Articles | Volume 10, issue 1
https://doi.org/10.5194/essd-10-303-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-10-303-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Peer-reviewed comment
| 
20 Feb 2018
Peer-reviewed comment |
| 20 Feb 2018
| 20 Feb 2018
Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014
Esteban Alonso-González
CORRESPONDING AUTHOR
Instituto Pirenaico de Ecología, Consejo Superior de
Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
J. Ignacio López-Moreno
Instituto Pirenaico de Ecología, Consejo Superior de
Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
Simon Gascoin
Centre d'Etudes Spatiales de la Biosphère (CESBIO),
UPS/CNRS/IRD/CNES, Toulouse, France
Matilde García-Valdecasas Ojeda
Departamento de Física Aplicada, Facultad de Ciencias,
Universidad de Granada, Granada, Spain
Alba Sanmiguel-Vallelado
Instituto Pirenaico de Ecología, Consejo Superior de
Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
Francisco Navarro-Serrano
Instituto Pirenaico de Ecología, Consejo Superior de
Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
Jesús Revuelto
Météo-France – CNRS, CNRM (UMR3589), Centre d'Etudes de la
Neige, Grenoble, France
Antonio Ceballos
Dept. Geografía, Universidad de Salamanca, Salamanca, Spain
María Jesús Esteban-Parra
Departamento de Física Aplicada, Facultad de Ciencias,
Universidad de Granada, Granada, Spain
Richard Essery
School of GeoSciences, University of Edinburgh, Edinburgh, UK
Related authors
Esteban Alonso-González, Adrian Harpold, Jessica D. Lundquist, Cara Piske, Laura Sourp, Kristoffer Aalstad, and Simon Gascoin
EGUsphere, https://doi.org/10.5194/egusphere-2025-2347, https://doi.org/10.5194/egusphere-2025-2347, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
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Simulating the snowpack is challenging, as there are several sources of uncertainty due to e.g. the meteorological forcing. Using data assimilation techniques, it is possible to improve the simulations by fusing models and snow observations. However in forests, observations are difficult to obtain, because they cannot be retrieved through the canopy. Here, we explore the possibility of propagating the information obtained in forest clearings to areas covered by the canopy.
Thibault Xavier, Laurent Orgogozo, Anatoly S. Prokushkin, Esteban Alonso-González, Simon Gascoin, and Oleg S. Pokrovsky
The Cryosphere, 18, 5865–5885, https://doi.org/10.5194/tc-18-5865-2024, https://doi.org/10.5194/tc-18-5865-2024, 2024
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Permafrost (permanently frozen soil at depth) is thawing as a result of climate change. However, estimating its future degradation is particularly challenging due to the complex multi-physical processes involved. In this work, we designed and ran numerical simulations for months on a supercomputer to quantify the impact of climate change in a forested valley of central Siberia. There, climate change could increase the thickness of the seasonally thawed soil layer in summer by up to 65 % by 2100.
Sara Arioli, Ghislain Picard, Laurent Arnaud, Simon Gascoin, Esteban Alonso-González, Marine Poizat, and Mark Irvine
Earth Syst. Sci. Data, 16, 3913–3934, https://doi.org/10.5194/essd-16-3913-2024, https://doi.org/10.5194/essd-16-3913-2024, 2024
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High-accuracy precision maps of the surface temperature of snow were acquired with an uncooled thermal-infrared camera during winter 2021–2022 and spring 2023. The accuracy – i.e., mean absolute error – improved from 1.28 K to 0.67 K between the seasons thanks to an improved camera setup and temperature stabilization. The dataset represents a major advance in the validation of satellite measurements and physical snow models over a complex topography.
Marco Mazzolini, Kristoffer Aalstad, Esteban Alonso-González, Sebastian Westermann, and Désirée Treichler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1404, https://doi.org/10.5194/egusphere-2024-1404, 2024
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In this work, we use the satellite laser altimeter ICESat-2 to retrieve snow depth in areas where snow amounts are still poorly estimated despite the high societal importance. We explore how to update snow models with these observations through algorithms that spatially propagate the information beyond the narrow satellite profiles. The positive results show the potential of this approach for improving snow simulations, both in terms of average snow depth and spatial distribution.
Josep Bonsoms, Juan I. López-Moreno, Esteban Alonso-González, César Deschamps-Berger, and Marc Oliva
Nat. Hazards Earth Syst. Sci., 24, 245–264, https://doi.org/10.5194/nhess-24-245-2024, https://doi.org/10.5194/nhess-24-245-2024, 2024
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Climate warming is changing mountain snowpack patterns, leading in some cases to rain-on-snow (ROS) events. Here we analyzed near-present ROS and its sensitivity to climate warming across the Pyrenees. ROS increases during the coldest months of the year but decreases in the warmest months and areas under severe warming due to snow cover depletion. Faster snow ablation is anticipated in the coldest and northern slopes of the range. Relevant implications in mountain ecosystem are anticipated.
Esteban Alonso-González, Kristoffer Aalstad, Norbert Pirk, Marco Mazzolini, Désirée Treichler, Paul Leclercq, Sebastian Westermann, Juan Ignacio López-Moreno, and Simon Gascoin
Hydrol. Earth Syst. Sci., 27, 4637–4659, https://doi.org/10.5194/hess-27-4637-2023, https://doi.org/10.5194/hess-27-4637-2023, 2023
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Here we explore how to improve hyper-resolution (5 m) distributed snowpack simulations using sparse observations, which do not provide information from all the areas of the simulation domain. We propose a new way of propagating information throughout the simulations adapted to the hyper-resolution, which could also be used to improve simulations of other nature. The method has been implemented in an open-source data assimilation tool that is readily accessible to everyone.
Esteban Alonso-González, Simon Gascoin, Sara Arioli, and Ghislain Picard
The Cryosphere, 17, 3329–3342, https://doi.org/10.5194/tc-17-3329-2023, https://doi.org/10.5194/tc-17-3329-2023, 2023
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Data assimilation techniques are a promising approach to improve snowpack simulations in remote areas that are difficult to monitor. This paper studies the ability of satellite-observed land surface temperature to improve snowpack simulations through data assimilation. We show that it is possible to improve snowpack simulations, but the temporal resolution of the observations and the algorithm used are critical to obtain satisfactory results.
Ixeia Vidaller, Eñaut Izagirre, Luis Mariano del Rio, Esteban Alonso-González, Francisco Rojas-Heredia, Enrique Serrano, Ana Moreno, Juan Ignacio López-Moreno, and Jesús Revuelto
The Cryosphere, 17, 3177–3192, https://doi.org/10.5194/tc-17-3177-2023, https://doi.org/10.5194/tc-17-3177-2023, 2023
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The Aneto glacier, the largest glacier in the Pyrenees, has shown continuous surface and ice thickness losses in the last decades. In this study, we examine changes in its surface and ice thickness for 1981–2022 and the remaining ice thickness in 2020. During these 41 years, the glacier has shrunk by 64.7 %, and the ice thickness has decreased by 30.5 m on average. The mean ice thickness in 2022 was 11.9 m, compared to 32.9 m in 1981. The results highlight the critical situation of the glacier.
Josep Bonsoms, Juan Ignacio López-Moreno, and Esteban Alonso-González
The Cryosphere, 17, 1307–1326, https://doi.org/10.5194/tc-17-1307-2023, https://doi.org/10.5194/tc-17-1307-2023, 2023
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This work analyzes the snow response to temperature and precipitation in the Pyrenees. During warm and wet seasons, seasonal snow depth is expected to be reduced by −37 %, −34 %, and −27 % per degree Celsius at low-, mid-, and high-elevation areas, respectively. The largest snow reductions are anticipated at low elevations of the eastern Pyrenees. Results anticipate important impacts on the nearby ecological and socioeconomic systems.
Esteban Alonso-González, Kristoffer Aalstad, Mohamed Wassim Baba, Jesús Revuelto, Juan Ignacio López-Moreno, Joel Fiddes, Richard Essery, and Simon Gascoin
Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, https://doi.org/10.5194/gmd-15-9127-2022, 2022
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Snow cover plays an important role in many processes, but its monitoring is a challenging task. The alternative is usually to simulate the snowpack, and to improve these simulations one of the most promising options is to fuse simulations with available observations (data assimilation). In this paper we present MuSA, a data assimilation tool which facilitates the implementation of snow monitoring initiatives, allowing the assimilation of a wide variety of remotely sensed snow cover information.
Esteban Alonso-González, Ethan Gutmann, Kristoffer Aalstad, Abbas Fayad, Marine Bouchet, and Simon Gascoin
Hydrol. Earth Syst. Sci., 25, 4455–4471, https://doi.org/10.5194/hess-25-4455-2021, https://doi.org/10.5194/hess-25-4455-2021, 2021
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Snow water resources represent a key hydrological resource for the Mediterranean regions, where most of the precipitation falls during the winter months. This is the case for Lebanon, where snowpack represents 31 % of the spring flow. We have used models to generate snow information corrected by means of remote sensing snow cover retrievals. Our results highlight the high temporal variability in the snowpack in Lebanon and its sensitivity to further warming caused by its hypsography.
Esteban Alonso-González and Víctor Fernández-García
Earth Syst. Sci. Data, 13, 1925–1938, https://doi.org/10.5194/essd-13-1925-2021, https://doi.org/10.5194/essd-13-1925-2021, 2021
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We present the first global burn severity database (MOSEV database), which is based on Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance and burned area products. The database inludes monthly scenes with the dNBR, RdNBR and post-burn NBR spectral indices at 500 m spatial resolution from November 2000 onwards. Moreover, in this work we show that there is a close relationship between the burn severity metrics included in MOSEV and the same ones obtained from Landsat-8.
Ana Moreno, Miguel Bartolomé, Juan Ignacio López-Moreno, Jorge Pey, Juan Pablo Corella, Jordi García-Orellana, Carlos Sancho, María Leunda, Graciela Gil-Romera, Penélope González-Sampériz, Carlos Pérez-Mejías, Francisco Navarro, Jaime Otero-García, Javier Lapazaran, Esteban Alonso-González, Cristina Cid, Jerónimo López-Martínez, Belén Oliva-Urcia, Sérgio Henrique Faria, María José Sierra, Rocío Millán, Xavier Querol, Andrés Alastuey, and José M. García-Ruíz
The Cryosphere, 15, 1157–1172, https://doi.org/10.5194/tc-15-1157-2021, https://doi.org/10.5194/tc-15-1157-2021, 2021
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Our study of the chronological sequence of Monte Perdido Glacier in the Central Pyrenees (Spain) reveals that, although the intense warming associated with the Roman period or Medieval Climate Anomaly produced important ice mass losses, it was insufficient to make this glacier disappear. By contrast, recent global warming has melted away almost 600 years of ice accumulated since the Little Ice Age, jeopardising the survival of this and other southern European glaciers over the next few decades.
Jesús Revuelto, Cesar Azorin-Molina, Esteban Alonso-González, Alba Sanmiguel-Vallelado, Francisco Navarro-Serrano, Ibai Rico, and Juan Ignacio López-Moreno
Earth Syst. Sci. Data, 9, 993–1005, https://doi.org/10.5194/essd-9-993-2017, https://doi.org/10.5194/essd-9-993-2017, 2017
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This work describes the snow and meteorological data set available for the Izas Experimental Catchment in the Central Spanish Pyrenees, from the 2011 to 2017 snow seasons. The climatic data set consists of (i) continuous meteorological variables acquired from an automatic weather station (AWS), (ii) detailed information on snow depth distribution collected with a terrestrial laser scanner for certain dates and (iii) time-lapse images showing the evolution of the snow-covered area.
Zacharie Barrou Dumont, Simon Gascoin, Jordi Inglada, Andreas Dietz, Jonas Köhler, Matthieu Lafaysse, Diego Monteiro, Carlo Carmagnola, Arthur Bayle, Jean-Pierre Dedieu, Olivier Hagolle, and Philippe Choler
The Cryosphere, 19, 2407–2429, https://doi.org/10.5194/tc-19-2407-2025, https://doi.org/10.5194/tc-19-2407-2025, 2025
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We generated annual maps of snow melt-out days at 20 m resolution over a period of 38 years from 10 different satellites. This study fills a knowledge gap regarding the evolution of mountain snow in Europe by covering a much longer period and characterizing trends at much higher resolutions than previous studies. We found a trend for earlier melt-out with average reductions of 5.51 d per decade over the French Alps and 4.04 d per decade over the Pyrenees for the period 1986–2023.
Matilde García-Valdecasas Ojeda, Feliciano Solano-Farias, David Donaire-Montaño, Emilio Romero-Jiménez, Juan José Rosa-Cánovas, Yolanda Castro-Díez, Sonia R. Gámiz-Fortis, and María Jesús Esteban-Parra
Earth Syst. Sci. Data, 17, 2809–2829, https://doi.org/10.5194/essd-17-2809-2025, https://doi.org/10.5194/essd-17-2809-2025, 2025
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This work aims to present a series of climate datasets for Sierra Nevada, a region especially vulnerable to climate change in southern Spain. The database consists of primary climate variables such as precipitation, temperature, radiation, wind speed, pressure, and atmospheric humidity and also bioclimatic variables and extreme indices, which are both useful pieces of information for assessing the impact of climate change in this region. These datasets are only available on Zenodo at https://doi.org/10.5281/zenodo.14883471.
Richard Essery, Giulia Mazzotti, Sarah Barr, Tobias Jonas, Tristan Quaife, and Nick Rutter
Geosci. Model Dev., 18, 3583–3605, https://doi.org/10.5194/gmd-18-3583-2025, https://doi.org/10.5194/gmd-18-3583-2025, 2025
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How forests influence accumulation and melt of snow on the ground is of long-standing interest, but uncertainty remains in how best to model forest snow processes. We developed the Flexible Snow Model version 2 to quantify these uncertainties. In a first model demonstration, how unloading of intercepted snow from the forest canopy is represented is responsible for the largest uncertainty. Global mapping of forest distribution is also likely to be a large source of uncertainty in existing models.
Esteban Alonso-González, Adrian Harpold, Jessica D. Lundquist, Cara Piske, Laura Sourp, Kristoffer Aalstad, and Simon Gascoin
EGUsphere, https://doi.org/10.5194/egusphere-2025-2347, https://doi.org/10.5194/egusphere-2025-2347, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
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Simulating the snowpack is challenging, as there are several sources of uncertainty due to e.g. the meteorological forcing. Using data assimilation techniques, it is possible to improve the simulations by fusing models and snow observations. However in forests, observations are difficult to obtain, because they cannot be retrieved through the canopy. Here, we explore the possibility of propagating the information obtained in forest clearings to areas covered by the canopy.
Josep Bonsoms, Marc Oliva, Juan Ignacio López-Moreno, and Guillaume Jouvet
The Cryosphere, 19, 1973–1993, https://doi.org/10.5194/tc-19-1973-2025, https://doi.org/10.5194/tc-19-1973-2025, 2025
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The extent to which Greenland's peripheral glaciers and ice caps current and future ice loss rates are unprecedented within the Holocene is poorly understood. This study connects the maximum ice extent of the Late Holocene with present and future glacier evolution in the Nuussuaq Peninsula (central western Greenland). By > 2050 glacier mass loss may have doubled in rate compared to the Late Holocene to the present, highlighting significant impacts of anthropogenic climate change.
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Julien Meloche, Benoit Montpetit, Nicolas R. Leroux, Richard Essery, Gabriel Hould Gosselin, and Philip Marsh
EGUsphere, https://doi.org/10.5194/egusphere-2025-1498, https://doi.org/10.5194/egusphere-2025-1498, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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The impact of uncertainties in the simulation of snow density and SSA by the snow model Crocus (embedded within the Soil, Vegetation and Snow version 2 land surface model) on the simulation of snow backscatter (13.5 GHz) using the Snow Microwave Radiative Transfer model were quantified. The simulation of SSA was found to be a key model uncertainty. Underestimated SSA values lead to high errors in the simulation of snow backscatter, reduced by implementing a minimum SSA value (8.7 m2 kg-1).
Léon Roussel, Marie Dumont, Marion Réveillet, Delphine Six, Marin Kneib, Pierre Nabat, Kevin Fourteau, Diego Monteiro, Simon Gascoin, Emmanuel Thibert, Antoine Rabatel, Jean-Emmanuel Sicart, Mylène Bonnefoy, Luc Piard, Olivier Laarman, Bruno Jourdain, Mathieu Fructus, Matthieu Vernay, and Matthieu Lafaysse
EGUsphere, https://doi.org/10.5194/egusphere-2025-1741, https://doi.org/10.5194/egusphere-2025-1741, 2025
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Saharan dust deposits frequently color alpine glaciers orange. Mineral dust reduces snow albedo and increases snow and glaciers melt rate. Using physical modeling, we quantified the impact of dust on the Argentière Glacier over the period 2019–2022. We found that that the contribution of mineral dust to the melt represents between 6 and 12 % of Argentière Glacier summer melt. At specific locations, the impact of dust over one year can rise to an equivalent of 1 meter of melted ice.
Carlos Sancho, Ánchel Belmonte, Maria Leunda, Marc Luetscher, Christoph Spötl, Juan Ignacio López-Moreno, Belén Oliva-Urcia, Jerónimo López-Martínez, Ana Moreno, and Miguel Bartolomé
EGUsphere, https://doi.org/10.5194/egusphere-2025-8, https://doi.org/10.5194/egusphere-2025-8, 2025
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Ice caves, vital for paleoclimate studies, face rapid ice loss due to global warming. A294 cave, home to the oldest firn deposit (6100 years BP), shows rising air temperatures (~1.07–1.56 °C in 12 years), fewer freezing days, and melting rates (15–192 cm/year). Key factors include warmer winters, increased rainfall, and reduced snowfall. This study highlights the urgency of recovering data from these unique ice archives before they vanish forever.
Helen Flynn, J. Julio Camarero, Alba Sanmiguel-Vallelado, Francisco Rojas Heredia, Pablo Domínguez Aguilar, Jesús Revuelto, and Juan Ignacio López-Moreno
Biogeosciences, 22, 1135–1147, https://doi.org/10.5194/bg-22-1135-2025, https://doi.org/10.5194/bg-22-1135-2025, 2025
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In the Spanish Pyrenees, changing snow seasons and warmer growing seasons could impact tree growth in the montane evergreen forests. We used automatic sensors that measure tree growth to monitor and analyze the interactions between the climate, snow, and tree growth at the study site. We found a transition in the daily growth cycle that is triggered by the presence of snow. Additionally, warmer February and May temperatures enhanced tree growth.
Laura Sourp, Simon Gascoin, Lionel Jarlan, Vanessa Pedinotti, Kat J. Bormann, and Mohamed Wassim Baba
Hydrol. Earth Syst. Sci., 29, 597–611, https://doi.org/10.5194/hess-29-597-2025, https://doi.org/10.5194/hess-29-597-2025, 2025
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Accurate knowledge of the spatial distribution of snow masses across landscapes is important for water management in mountain catchments. We present a new tool for estimating snow water resources without ground measurements. We evaluate the output of this tool using accurate airborne measurements in the Sierra Nevada and find that it provides realistic estimates of snow mass and snow depth at the catchment scale.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci., 28, 5331–5352, https://doi.org/10.5194/hess-28-5331-2024, https://doi.org/10.5194/hess-28-5331-2024, 2024
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Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. We investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analyses indicate that adding two vegetation parameters is enough to improve the representation of evaporation and that the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Thibault Xavier, Laurent Orgogozo, Anatoly S. Prokushkin, Esteban Alonso-González, Simon Gascoin, and Oleg S. Pokrovsky
The Cryosphere, 18, 5865–5885, https://doi.org/10.5194/tc-18-5865-2024, https://doi.org/10.5194/tc-18-5865-2024, 2024
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Permafrost (permanently frozen soil at depth) is thawing as a result of climate change. However, estimating its future degradation is particularly challenging due to the complex multi-physical processes involved. In this work, we designed and ran numerical simulations for months on a supercomputer to quantify the impact of climate change in a forested valley of central Siberia. There, climate change could increase the thickness of the seasonally thawed soil layer in summer by up to 65 % by 2100.
Ixeia Vidaller, Toshiyuki Fujioka, Juan Ignacio López-Moreno, Ana Moreno, and the ASTER Team
Clim. Past Discuss., https://doi.org/10.5194/cp-2024-75, https://doi.org/10.5194/cp-2024-75, 2024
Preprint under review for CP
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Since the Pyrenean Last Glacial Maximum (75 ka), the deglaciation of the Ésera glacier (central Pyrenees) was characterized by complex dynamics, with advances and rapid retreats. Cosmogenic dates of moraines along the headwaters of the valley and lacustrine sediments analyses allowed to reconstruct evolutionary history of the Ésera glacier and the associated environmental implications during the last deglaciation and calculate the Equilibrium Line Altitude to determine changes in temperature.
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Richard Essery, Philip Marsh, Rosamond Tutton, Branden Walker, Matthieu Lafaysse, and David Pritchard
The Cryosphere, 18, 5685–5711, https://doi.org/10.5194/tc-18-5685-2024, https://doi.org/10.5194/tc-18-5685-2024, 2024
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Parameterisations of Arctic snow processes were implemented into the multi-physics ensemble version of the snow model Crocus (embedded within the Soil, Vegetation, and Snow version 2 land surface model) and evaluated at an Arctic tundra site. Optimal combinations of parameterisations that improved the simulation of density and specific surface area featured modifications that raise wind speeds to increase compaction in surface layers, prevent snowdrift, and increase viscosity in basal layers.
Cecile B. Menard, Sirpa Rasmus, Ioanna Merkouriadi, Gianpaolo Balsamo, Annett Bartsch, Chris Derksen, Florent Domine, Marie Dumont, Dorothee Ehrich, Richard Essery, Bruce C. Forbes, Gerhard Krinner, David Lawrence, Glen Liston, Heidrun Matthes, Nick Rutter, Melody Sandells, Martin Schneebeli, and Sari Stark
The Cryosphere, 18, 4671–4686, https://doi.org/10.5194/tc-18-4671-2024, https://doi.org/10.5194/tc-18-4671-2024, 2024
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Computer models, like those used in climate change studies, are written by modellers who have to decide how best to construct the models in order to satisfy the purpose they serve. Using snow modelling as an example, we examine the process behind the decisions to understand what motivates or limits modellers in their decision-making. We find that the context in which research is undertaken is often more crucial than scientific limitations. We argue for more transparency in our research practice.
Melody Sandells, Nick Rutter, Kirsty Wivell, Richard Essery, Stuart Fox, Chawn Harlow, Ghislain Picard, Alexandre Roy, Alain Royer, and Peter Toose
The Cryosphere, 18, 3971–3990, https://doi.org/10.5194/tc-18-3971-2024, https://doi.org/10.5194/tc-18-3971-2024, 2024
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Satellite microwave observations are used for weather forecasting. In Arctic regions this is complicated by natural emission from snow. By simulating airborne observations from in situ measurements of snow, this study shows how snow properties affect the signal within the atmosphere. Fresh snowfall between flights changed airborne measurements. Good knowledge of snow layering and structure can be used to account for the effects of snow and could unlock these data to improve forecasts.
Sara Arioli, Ghislain Picard, Laurent Arnaud, Simon Gascoin, Esteban Alonso-González, Marine Poizat, and Mark Irvine
Earth Syst. Sci. Data, 16, 3913–3934, https://doi.org/10.5194/essd-16-3913-2024, https://doi.org/10.5194/essd-16-3913-2024, 2024
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High-accuracy precision maps of the surface temperature of snow were acquired with an uncooled thermal-infrared camera during winter 2021–2022 and spring 2023. The accuracy – i.e., mean absolute error – improved from 1.28 K to 0.67 K between the seasons thanks to an improved camera setup and temperature stabilization. The dataset represents a major advance in the validation of satellite measurements and physical snow models over a complex topography.
Ange Haddjeri, Matthieu Baron, Matthieu Lafaysse, Louis Le Toumelin, César Deschamps-Berger, Vincent Vionnet, Simon Gascoin, Matthieu Vernay, and Marie Dumont
The Cryosphere, 18, 3081–3116, https://doi.org/10.5194/tc-18-3081-2024, https://doi.org/10.5194/tc-18-3081-2024, 2024
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Our study addresses the complex challenge of evaluating distributed alpine snow simulations with snow transport against snow depths from Pléiades stereo imagery and snow melt-out dates from Sentinel-2 and Landsat-8 satellites. Additionally, we disentangle error contributions between blowing snow, precipitation heterogeneity, and unresolved subgrid variability. Snow transport enhances the snow simulations at high elevations, while precipitation biases are the main error source in other areas.
Julien Meloche, Melody Sandells, Henning Löwe, Nick Rutter, Richard Essery, Ghislain Picard, Randall K. Scharien, Alexandre Langlois, Matthias Jaggi, Josh King, Peter Toose, Jérôme Bouffard, Alessandro Di Bella, and Michele Scagliola
EGUsphere, https://doi.org/10.5194/egusphere-2024-1583, https://doi.org/10.5194/egusphere-2024-1583, 2024
Preprint archived
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Sea ice thickness is essential for climate studies. Radar altimetry has provided sea ice thickness measurement, but uncertainty arises from interaction of the signal with the snow cover. Therefore, modelling the signal interaction with the snow is necessary to improve retrieval. A radar model was used to simulate the radar signal from the snow-covered sea ice. This work paved the way to improved physical algorithm to retrieve snow depth and sea ice thickness for radar altimeter missions.
Marco Mazzolini, Kristoffer Aalstad, Esteban Alonso-González, Sebastian Westermann, and Désirée Treichler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1404, https://doi.org/10.5194/egusphere-2024-1404, 2024
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In this work, we use the satellite laser altimeter ICESat-2 to retrieve snow depth in areas where snow amounts are still poorly estimated despite the high societal importance. We explore how to update snow models with these observations through algorithms that spatially propagate the information beyond the narrow satellite profiles. The positive results show the potential of this approach for improving snow simulations, both in terms of average snow depth and spatial distribution.
Lahoucine Hanich, Ouiaam Lahnik, Simon Gascoin, Adnane Chakir, and Vincent Simonneaux
Proc. IAHS, 385, 387–391, https://doi.org/10.5194/piahs-385-387-2024, https://doi.org/10.5194/piahs-385-387-2024, 2024
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Using a dataset measured with the eddy covariance system (EC) for a period from September 2020 to January 2021 at the Tazaghart plateau, located in the High Atlas of Marrakech, the sublimation was estimated. The average daily sublimation rate measured was 0.41 mm per day. Measured sublimation accounted for 42 % and 40 % of snow ablation, based on the energy and water balances, respectively.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024, https://doi.org/10.5194/bg-21-825-2024, 2024
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We undertake a sensitivity study of three different parameters on the simulation of net ecosystem exchange (NEE) during the snow-covered non-growing season at an Arctic tundra site. Simulations are compared to eddy covariance measurements, with near-zero NEE simulated despite observed CO2 release. We then consider how to parameterise the model better in Arctic tundra environments on both sub-seasonal timescales and cumulatively throughout the snow-covered non-growing season.
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024, https://doi.org/10.5194/gmd-17-911-2024, 2024
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We present a parsimonious snow model which simulates snow mass without the need for extensive calibration. The model is based on a machine learning algorithm that has been trained on diverse set of daily observations of snow accumulation or melt, along with corresponding climate and topography data. We validated the model using in situ data from numerous new locations. The model provides a promising solution for accurate snow mass estimation across regions where in situ data are limited.
Josep Bonsoms, Juan I. López-Moreno, Esteban Alonso-González, César Deschamps-Berger, and Marc Oliva
Nat. Hazards Earth Syst. Sci., 24, 245–264, https://doi.org/10.5194/nhess-24-245-2024, https://doi.org/10.5194/nhess-24-245-2024, 2024
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Climate warming is changing mountain snowpack patterns, leading in some cases to rain-on-snow (ROS) events. Here we analyzed near-present ROS and its sensitivity to climate warming across the Pyrenees. ROS increases during the coldest months of the year but decreases in the warmest months and areas under severe warming due to snow cover depletion. Faster snow ablation is anticipated in the coldest and northern slopes of the range. Relevant implications in mountain ecosystem are anticipated.
Esteban Alonso-González, Kristoffer Aalstad, Norbert Pirk, Marco Mazzolini, Désirée Treichler, Paul Leclercq, Sebastian Westermann, Juan Ignacio López-Moreno, and Simon Gascoin
Hydrol. Earth Syst. Sci., 27, 4637–4659, https://doi.org/10.5194/hess-27-4637-2023, https://doi.org/10.5194/hess-27-4637-2023, 2023
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Here we explore how to improve hyper-resolution (5 m) distributed snowpack simulations using sparse observations, which do not provide information from all the areas of the simulation domain. We propose a new way of propagating information throughout the simulations adapted to the hyper-resolution, which could also be used to improve simulations of other nature. The method has been implemented in an open-source data assimilation tool that is readily accessible to everyone.
Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, https://doi.org/10.5194/essd-15-5121-2023, 2023
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Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Two field campaigns during the winters 2016–17 and 2017–18 were conducted in a coniferous forest in the French Alps to study interactions between snow and vegetation. This paper presents the field site, instrumentation and collection methods. The observations include forest characteristics, meteorology, snow cover and snow interception by the canopy during precipitation events.
Kirsty Wivell, Stuart Fox, Melody Sandells, Chawn Harlow, Richard Essery, and Nick Rutter
The Cryosphere, 17, 4325–4341, https://doi.org/10.5194/tc-17-4325-2023, https://doi.org/10.5194/tc-17-4325-2023, 2023
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Satellite microwave observations improve weather forecasts, but to use these observations in the Arctic, snow emission must be known. This study uses airborne and in situ snow observations to validate emissivity simulations for two- and three-layer snowpacks at key frequencies for weather prediction. We assess the impact of thickness, grain size and density in key snow layers, which will help inform development of physical snow models that provide snow profile input to emissivity simulations.
Esteban Alonso-González, Simon Gascoin, Sara Arioli, and Ghislain Picard
The Cryosphere, 17, 3329–3342, https://doi.org/10.5194/tc-17-3329-2023, https://doi.org/10.5194/tc-17-3329-2023, 2023
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Data assimilation techniques are a promising approach to improve snowpack simulations in remote areas that are difficult to monitor. This paper studies the ability of satellite-observed land surface temperature to improve snowpack simulations through data assimilation. We show that it is possible to improve snowpack simulations, but the temporal resolution of the observations and the algorithm used are critical to obtain satisfactory results.
Ixeia Vidaller, Eñaut Izagirre, Luis Mariano del Rio, Esteban Alonso-González, Francisco Rojas-Heredia, Enrique Serrano, Ana Moreno, Juan Ignacio López-Moreno, and Jesús Revuelto
The Cryosphere, 17, 3177–3192, https://doi.org/10.5194/tc-17-3177-2023, https://doi.org/10.5194/tc-17-3177-2023, 2023
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The Aneto glacier, the largest glacier in the Pyrenees, has shown continuous surface and ice thickness losses in the last decades. In this study, we examine changes in its surface and ice thickness for 1981–2022 and the remaining ice thickness in 2020. During these 41 years, the glacier has shrunk by 64.7 %, and the ice thickness has decreased by 30.5 m on average. The mean ice thickness in 2022 was 11.9 m, compared to 32.9 m in 1981. The results highlight the critical situation of the glacier.
Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
Earth Syst. Sci. Data, 15, 3075–3094, https://doi.org/10.5194/essd-15-3075-2023, https://doi.org/10.5194/essd-15-3075-2023, 2023
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Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
César Deschamps-Berger, Simon Gascoin, David Shean, Hannah Besso, Ambroise Guiot, and Juan Ignacio López-Moreno
The Cryosphere, 17, 2779–2792, https://doi.org/10.5194/tc-17-2779-2023, https://doi.org/10.5194/tc-17-2779-2023, 2023
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The estimation of the snow depth in mountains is hard, despite the importance of the snowpack for human societies and ecosystems. We measured the snow depth in mountains by comparing the elevation of points measured with snow from the high-precision altimetric satellite ICESat-2 to the elevation without snow from various sources. Snow depths derived only from ICESat-2 were too sparse, but using external airborne/satellite products results in spatially richer and sufficiently precise snow depths.
Arthur Bayle, Bradley Z. Carlson, Anaïs Zimmer, Sophie Vallée, Antoine Rabatel, Edoardo Cremonese, Gianluca Filippa, Cédric Dentant, Christophe Randin, Andrea Mainetti, Erwan Roussel, Simon Gascoin, Dov Corenblit, and Philippe Choler
Biogeosciences, 20, 1649–1669, https://doi.org/10.5194/bg-20-1649-2023, https://doi.org/10.5194/bg-20-1649-2023, 2023
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Glacier forefields have long provided ecologists with a model to study patterns of plant succession following glacier retreat. We used remote sensing approaches to study early succession dynamics as it allows to analyze the deglaciation, colonization, and vegetation growth within a single framework. We found that the heterogeneity of early succession dynamics is deterministic and can be explained well by local environmental context. This work has been done by an international consortium.
Josep Bonsoms, Juan Ignacio López-Moreno, and Esteban Alonso-González
The Cryosphere, 17, 1307–1326, https://doi.org/10.5194/tc-17-1307-2023, https://doi.org/10.5194/tc-17-1307-2023, 2023
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This work analyzes the snow response to temperature and precipitation in the Pyrenees. During warm and wet seasons, seasonal snow depth is expected to be reduced by −37 %, −34 %, and −27 % per degree Celsius at low-, mid-, and high-elevation areas, respectively. The largest snow reductions are anticipated at low elevations of the eastern Pyrenees. Results anticipate important impacts on the nearby ecological and socioeconomic systems.
Miguel Bartolomé, Gérard Cazenave, Marc Luetscher, Christoph Spötl, Fernando Gázquez, Ánchel Belmonte, Alexandra V. Turchyn, Juan Ignacio López-Moreno, and Ana Moreno
The Cryosphere, 17, 477–497, https://doi.org/10.5194/tc-17-477-2023, https://doi.org/10.5194/tc-17-477-2023, 2023
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In this work we study the microclimate and the geomorphological features of Devaux ice cave in the Central Pyrenees. The research is based on cave monitoring, geomorphology, and geochemical analyses. We infer two different thermal regimes. The cave is impacted by flooding in late winter/early spring when the main outlets freeze, damming the water inside. Rock temperatures below 0°C and the absence of drip water indicate frozen rock, while relict ice formations record past damming events.
Esteban Alonso-González, Kristoffer Aalstad, Mohamed Wassim Baba, Jesús Revuelto, Juan Ignacio López-Moreno, Joel Fiddes, Richard Essery, and Simon Gascoin
Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, https://doi.org/10.5194/gmd-15-9127-2022, 2022
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Snow cover plays an important role in many processes, but its monitoring is a challenging task. The alternative is usually to simulate the snowpack, and to improve these simulations one of the most promising options is to fuse simulations with available observations (data assimilation). In this paper we present MuSA, a data assimilation tool which facilitates the implementation of snow monitoring initiatives, allowing the assimilation of a wide variety of remotely sensed snow cover information.
Maximillian Van Wyk de Vries, Shashank Bhushan, Mylène Jacquemart, César Deschamps-Berger, Etienne Berthier, Simon Gascoin, David E. Shean, Dan H. Shugar, and Andreas Kääb
Nat. Hazards Earth Syst. Sci., 22, 3309–3327, https://doi.org/10.5194/nhess-22-3309-2022, https://doi.org/10.5194/nhess-22-3309-2022, 2022
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On 7 February 2021, a large rock–ice avalanche occurred in Chamoli, Indian Himalaya. The resulting debris flow swept down the nearby valley, leaving over 200 people dead or missing. We use a range of satellite datasets to investigate how the collapse area changed prior to collapse. We show that signs of instability were visible as early 5 years prior to collapse. However, it would likely not have been possible to predict the timing of the event from current satellite datasets.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Melody Sandells, Chris Derksen, Branden Walker, Gabriel Hould Gosselin, Oliver Sonnentag, Richard Essery, Richard Kelly, Phillip Marsh, Joshua King, and Julia Boike
The Cryosphere, 16, 4201–4222, https://doi.org/10.5194/tc-16-4201-2022, https://doi.org/10.5194/tc-16-4201-2022, 2022
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Measurements of the properties of the snow and soil were compared to simulations of the Community Land Model to see how well the model represents snow insulation. Simulations underestimated snow thermal conductivity and wintertime soil temperatures. We test two approaches to reduce the transfer of heat through the snowpack and bring simulated soil temperatures closer to measurements, with an alternative parameterisation of snow thermal conductivity being more appropriate.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
Earth Syst. Sci. Data, 14, 3915–3945, https://doi.org/10.5194/essd-14-3915-2022, https://doi.org/10.5194/essd-14-3915-2022, 2022
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The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
Zacharie Barrou Dumont, Simon Gascoin, Olivier Hagolle, Michaël Ablain, Rémi Jugier, Germain Salgues, Florence Marti, Aurore Dupuis, Marie Dumont, and Samuel Morin
The Cryosphere, 15, 4975–4980, https://doi.org/10.5194/tc-15-4975-2021, https://doi.org/10.5194/tc-15-4975-2021, 2021
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Since 2020, the Copernicus High Resolution Snow & Ice Monitoring Service has distributed snow cover maps at 20 m resolution over Europe in near-real time. These products are derived from the Sentinel-2 Earth observation mission, with a revisit time of 5 d or less (cloud-permitting). Here we show the good accuracy of the snow detection over a wide range of regions in Europe, except in dense forest regions where the snow cover is hidden by the trees.
Nora Helbig, Michael Schirmer, Jan Magnusson, Flavia Mäder, Alec van Herwijnen, Louis Quéno, Yves Bühler, Jeff S. Deems, and Simon Gascoin
The Cryosphere, 15, 4607–4624, https://doi.org/10.5194/tc-15-4607-2021, https://doi.org/10.5194/tc-15-4607-2021, 2021
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The snow cover spatial variability in mountains changes considerably over the course of a snow season. In applications such as weather, climate and hydrological predictions the fractional snow-covered area is therefore an essential parameter characterizing how much of the ground surface in a grid cell is currently covered by snow. We present a seasonal algorithm and a spatiotemporal evaluation suggesting that the algorithm can be applied in other geographic regions by any snow model application.
Esteban Alonso-González, Ethan Gutmann, Kristoffer Aalstad, Abbas Fayad, Marine Bouchet, and Simon Gascoin
Hydrol. Earth Syst. Sci., 25, 4455–4471, https://doi.org/10.5194/hess-25-4455-2021, https://doi.org/10.5194/hess-25-4455-2021, 2021
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Snow water resources represent a key hydrological resource for the Mediterranean regions, where most of the precipitation falls during the winter months. This is the case for Lebanon, where snowpack represents 31 % of the spring flow. We have used models to generate snow information corrected by means of remote sensing snow cover retrievals. Our results highlight the high temporal variability in the snowpack in Lebanon and its sensitivity to further warming caused by its hypsography.
Esteban Alonso-González and Víctor Fernández-García
Earth Syst. Sci. Data, 13, 1925–1938, https://doi.org/10.5194/essd-13-1925-2021, https://doi.org/10.5194/essd-13-1925-2021, 2021
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We present the first global burn severity database (MOSEV database), which is based on Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance and burned area products. The database inludes monthly scenes with the dNBR, RdNBR and post-burn NBR spectral indices at 500 m spatial resolution from November 2000 onwards. Moreover, in this work we show that there is a close relationship between the burn severity metrics included in MOSEV and the same ones obtained from Landsat-8.
Andreas Kääb, Mylène Jacquemart, Adrien Gilbert, Silvan Leinss, Luc Girod, Christian Huggel, Daniel Falaschi, Felipe Ugalde, Dmitry Petrakov, Sergey Chernomorets, Mikhail Dokukin, Frank Paul, Simon Gascoin, Etienne Berthier, and Jeffrey S. Kargel
The Cryosphere, 15, 1751–1785, https://doi.org/10.5194/tc-15-1751-2021, https://doi.org/10.5194/tc-15-1751-2021, 2021
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Hardly recognized so far, giant catastrophic detachments of glaciers are a rare but great potential for loss of lives and massive damage in mountain regions. Several of the events compiled in our study involve volumes (up to 100 million m3 and more), avalanche speeds (up to 300 km/h), and reaches (tens of kilometres) that are hard to imagine. We show that current climate change is able to enhance associated hazards. For the first time, we elaborate a set of factors that could cause these events.
Ana Moreno, Miguel Bartolomé, Juan Ignacio López-Moreno, Jorge Pey, Juan Pablo Corella, Jordi García-Orellana, Carlos Sancho, María Leunda, Graciela Gil-Romera, Penélope González-Sampériz, Carlos Pérez-Mejías, Francisco Navarro, Jaime Otero-García, Javier Lapazaran, Esteban Alonso-González, Cristina Cid, Jerónimo López-Martínez, Belén Oliva-Urcia, Sérgio Henrique Faria, María José Sierra, Rocío Millán, Xavier Querol, Andrés Alastuey, and José M. García-Ruíz
The Cryosphere, 15, 1157–1172, https://doi.org/10.5194/tc-15-1157-2021, https://doi.org/10.5194/tc-15-1157-2021, 2021
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Our study of the chronological sequence of Monte Perdido Glacier in the Central Pyrenees (Spain) reveals that, although the intense warming associated with the Roman period or Medieval Climate Anomaly produced important ice mass losses, it was insufficient to make this glacier disappear. By contrast, recent global warming has melted away almost 600 years of ice accumulated since the Little Ice Age, jeopardising the survival of this and other southern European glaciers over the next few decades.
Vincent Vionnet, Christopher B. Marsh, Brian Menounos, Simon Gascoin, Nicholas E. Wayand, Joseph Shea, Kriti Mukherjee, and John W. Pomeroy
The Cryosphere, 15, 743–769, https://doi.org/10.5194/tc-15-743-2021, https://doi.org/10.5194/tc-15-743-2021, 2021
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Mountain snow cover provides critical supplies of fresh water to downstream users. Its accurate prediction requires inclusion of often-ignored processes. A multi-scale modelling strategy is presented that efficiently accounts for snow redistribution. Model accuracy is assessed via airborne lidar and optical satellite imagery. With redistribution the model captures the elevation–snow depth relation. Redistribution processes are required to reproduce spatial variability, such as around ridges.
Nora Helbig, Yves Bühler, Lucie Eberhard, César Deschamps-Berger, Simon Gascoin, Marie Dumont, Jesus Revuelto, Jeff S. Deems, and Tobias Jonas
The Cryosphere, 15, 615–632, https://doi.org/10.5194/tc-15-615-2021, https://doi.org/10.5194/tc-15-615-2021, 2021
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The spatial variability in snow depth in mountains is driven by interactions between topography, wind, precipitation and radiation. In applications such as weather, climate and hydrological predictions, this is accounted for by the fractional snow-covered area describing the fraction of the ground surface covered by snow. We developed a new description for model grid cell sizes larger than 200 m. An evaluation suggests that the description performs similarly well in most geographical regions.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
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Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
François Tuzet, Marie Dumont, Ghislain Picard, Maxim Lamare, Didier Voisin, Pierre Nabat, Mathieu Lafaysse, Fanny Larue, Jesus Revuelto, and Laurent Arnaud
The Cryosphere, 14, 4553–4579, https://doi.org/10.5194/tc-14-4553-2020, https://doi.org/10.5194/tc-14-4553-2020, 2020
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This study presents a field dataset collected over 30 d from two snow seasons at a Col du Lautaret site (French Alps). The dataset compares different measurements or estimates of light-absorbing particle (LAP) concentrations in snow, highlighting a gap in the current understanding of the measurement of these quantities. An ensemble snowpack model is then evaluated for this dataset estimating that LAPs shorten each snow season by around 10 d despite contrasting meteorological conditions.
El Mahdi El Khalki, Yves Tramblay, Christian Massari, Luca Brocca, Vincent Simonneaux, Simon Gascoin, and Mohamed El Mehdi Saidi
Nat. Hazards Earth Syst. Sci., 20, 2591–2607, https://doi.org/10.5194/nhess-20-2591-2020, https://doi.org/10.5194/nhess-20-2591-2020, 2020
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In North Africa, the vulnerability to floods is high, and there is a need to improve the flood-forecasting systems. Remote-sensing and reanalysis data can palliate the lack of in situ measurements, in particular for soil moisture, which is a crucial parameter to consider when modeling floods. In this study we provide an evaluation of recent globally available soil moisture products for flood modeling in Morocco.
César Deschamps-Berger, Simon Gascoin, Etienne Berthier, Jeffrey Deems, Ethan Gutmann, Amaury Dehecq, David Shean, and Marie Dumont
The Cryosphere, 14, 2925–2940, https://doi.org/10.5194/tc-14-2925-2020, https://doi.org/10.5194/tc-14-2925-2020, 2020
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We evaluate a recent method to map snow depth based on satellite photogrammetry. We compare it with accurate airborne laser-scanning measurements in the Sierra Nevada, USA. We find that satellite data capture the relationship between snow depth and elevation at the catchment scale and also small-scale features like snow drifts and avalanche deposits. We conclude that satellite photogrammetry stands out as a convenient method to estimate the spatial distribution of snow depth in high mountains.
C. Abou Chakra, J. Somma, S. Gascoin, P. Fanise, and L. Drapeau
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 119–125, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-119-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-119-2020, 2020
Lawrence Mudryk, María Santolaria-Otín, Gerhard Krinner, Martin Ménégoz, Chris Derksen, Claire Brutel-Vuilmet, Mike Brady, and Richard Essery
The Cryosphere, 14, 2495–2514, https://doi.org/10.5194/tc-14-2495-2020, https://doi.org/10.5194/tc-14-2495-2020, 2020
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We analyze how well updated state-of-the-art climate models reproduce observed historical snow cover extent and snow mass and how they project that these quantities will change up to the year 2100. Overall the updated models better represent historical snow extent than previous models, and they simulate stronger historical trends in snow extent and snow mass. They project that spring snow extent will decrease by 8 % for each degree Celsius that the global surface air temperature increases.
Michael Kern, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, Arnaud Lecuyot, Michael Ludwig, Rolv Midthassel, Ignacio Navas Traver, Tommaso Parrinello, Gerhard Ressler, Erik Andersson, Cristina Martin-Puig, Ole Andersen, Annett Bartsch, Sinead Farrell, Sara Fleury, Simon Gascoin, Amandine Guillot, Angelika Humbert, Eero Rinne, Andrew Shepherd, Michiel R. van den Broeke, and John Yackel
The Cryosphere, 14, 2235–2251, https://doi.org/10.5194/tc-14-2235-2020, https://doi.org/10.5194/tc-14-2235-2020, 2020
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The Copernicus Polar Ice and Snow Topography Altimeter will provide high-resolution sea ice thickness and land ice elevation measurements and the capability to determine the properties of snow cover on ice to serve operational products and services of direct relevance to the polar regions. This paper describes the mission objectives, identifies the key contributions the CRISTAL mission will make, and presents a concept – as far as it is already defined – for the mission payload.
Fanny Larue, Ghislain Picard, Laurent Arnaud, Inès Ollivier, Clément Delcourt, Maxim Lamare, François Tuzet, Jesus Revuelto, and Marie Dumont
The Cryosphere, 14, 1651–1672, https://doi.org/10.5194/tc-14-1651-2020, https://doi.org/10.5194/tc-14-1651-2020, 2020
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The effect of surface roughness on snow albedo is often overlooked,
although a small change in albedo may strongly affect the surface energy
budget. By carving artificial roughness in an initially smooth snowpack,
we highlight albedo reductions of 0.03–0.04 at 700 nm and 0.06–0.10 at 1000 nm. A model using photon transport is developed to compute albedo considering roughness and applied to understand the impact of roughness as a function of snow properties and illumination conditions.
Abbas Fayad and Simon Gascoin
Hydrol. Earth Syst. Sci., 24, 1527–1542, https://doi.org/10.5194/hess-24-1527-2020, https://doi.org/10.5194/hess-24-1527-2020, 2020
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Seasonal snowpack is an essential water resource in Mediterranean mountains. Here, we look at the role of water percolation in simulating snow mass (SWE), for the first time, in Mount Lebanon. We use SnowModel, a distributed snow model, forced by station data. The main sources of uncertainty were attributed to rain–snow partitioning, transient winter snowmelt, and the subpixel snow cover. Yet, we show that a process-based model is suitable to simulate wet snowpack in Mediterranean mountains.
Marion Réveillet, Shelley MacDonell, Simon Gascoin, Christophe Kinnard, Stef Lhermitte, and Nicole Schaffer
The Cryosphere, 14, 147–163, https://doi.org/10.5194/tc-14-147-2020, https://doi.org/10.5194/tc-14-147-2020, 2020
Nick Rutter, Melody J. Sandells, Chris Derksen, Joshua King, Peter Toose, Leanne Wake, Tom Watts, Richard Essery, Alexandre Roy, Alain Royer, Philip Marsh, Chris Larsen, and Matthew Sturm
The Cryosphere, 13, 3045–3059, https://doi.org/10.5194/tc-13-3045-2019, https://doi.org/10.5194/tc-13-3045-2019, 2019
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Impact of natural variability in Arctic tundra snow microstructural characteristics on the capacity to estimate snow water equivalent (SWE) from Ku-band radar was assessed. Median values of metrics quantifying snow microstructure adequately characterise differences between snowpack layers. Optimal estimates of SWE required microstructural values slightly less than the measured median but tolerated natural variability for accurate estimation of SWE in shallow snowpacks.
Francois Tuzet, Marie Dumont, Laurent Arnaud, Didier Voisin, Maxim Lamare, Fanny Larue, Jesus Revuelto, and Ghislain Picard
The Cryosphere, 13, 2169–2187, https://doi.org/10.5194/tc-13-2169-2019, https://doi.org/10.5194/tc-13-2169-2019, 2019
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Here we present a novel method to estimate the impurity content (e.g. black carbon or mineral dust) in Alpine snow based on measurements of light extinction profiles. This method is proposed as an alternative to chemical measurements, allowing rapid retrievals of vertical concentrations of impurities in the snowpack. In addition, the results provide a better understanding of the impact of impurities on visible light extinction in snow.
S. Ferrant, A. Selles, M. Le Page, A. AlBitar, S. Mermoz, S. Gascoin, A. Bouvet, S. Ahmed, and Y. Kerr
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W6, 285–292, https://doi.org/10.5194/isprs-archives-XLII-3-W6-285-2019, https://doi.org/10.5194/isprs-archives-XLII-3-W6-285-2019, 2019
David Walters, Anthony J. Baran, Ian Boutle, Malcolm Brooks, Paul Earnshaw, John Edwards, Kalli Furtado, Peter Hill, Adrian Lock, James Manners, Cyril Morcrette, Jane Mulcahy, Claudio Sanchez, Chris Smith, Rachel Stratton, Warren Tennant, Lorenzo Tomassini, Kwinten Van Weverberg, Simon Vosper, Martin Willett, Jo Browse, Andrew Bushell, Kenneth Carslaw, Mohit Dalvi, Richard Essery, Nicola Gedney, Steven Hardiman, Ben Johnson, Colin Johnson, Andy Jones, Colin Jones, Graham Mann, Sean Milton, Heather Rumbold, Alistair Sellar, Masashi Ujiie, Michael Whitall, Keith Williams, and Mohamed Zerroukat
Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, https://doi.org/10.5194/gmd-12-1909-2019, 2019
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Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of JULES are developed for use in any global atmospheric modelling application. We describe a recent iteration of these configurations, GA7/GL7, which includes new aerosol and snow schemes and addresses the four critical errors identified in GA6. GA7/GL7 will underpin the UK's contributions to CMIP6, and hence their documentation is important.
Simon Gascoin, Manuel Grizonnet, Marine Bouchet, Germain Salgues, and Olivier Hagolle
Earth Syst. Sci. Data, 11, 493–514, https://doi.org/10.5194/essd-11-493-2019, https://doi.org/10.5194/essd-11-493-2019, 2019
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The Sentinel-2 satellite mission allows the observation of the land surface at unprecedented resolutions (20 m every 5 days). The frequency of observations can be further increased with Landsat-8. Here we describe a new collection of snow maps made from Sentinel-2 and Landsat-8 and evaluate their accuracy. The data are routinely produced over several mountain areas and freely distributed via http://theia.cnes.fr. These new data could unlock advances in our understanding of mountain ecosystems.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
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This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Adrien Gilbert, Silvan Leinss, Jeffrey Kargel, Andreas Kääb, Simon Gascoin, Gregory Leonard, Etienne Berthier, Alina Karki, and Tandong Yao
The Cryosphere, 12, 2883–2900, https://doi.org/10.5194/tc-12-2883-2018, https://doi.org/10.5194/tc-12-2883-2018, 2018
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In Tibet, two glaciers suddenly collapsed in summer 2016 and produced two gigantic ice avalanches, killing nine people. This kind of phenomenon is extremely rare. By combining a detailed modelling study and high-resolution satellite observations, we show that the event was triggered by an increasing meltwater supply in the fine-grained material underneath the two glaciers. Contrary to what is often thought, this event is not linked to a change in the thermal condition at the glacier base.
Brett Woelber, Marco P. Maneta, Joel Harper, Kelsey G. Jencso, W. Payton Gardner, Andrew C. Wilcox, and Ignacio López-Moreno
Hydrol. Earth Syst. Sci., 22, 4295–4310, https://doi.org/10.5194/hess-22-4295-2018, https://doi.org/10.5194/hess-22-4295-2018, 2018
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The hydrology of high-elevation headwaters in midlatitudes is typically dominated by snow processes, which are very sensitive to changes in energy inputs at the top of the snowpack. We present a data analyses that reveal how snowmelt and transpiration waves induced by the diurnal solar cycle generate water pressure fluctuations that propagate through the snowpack–hillslope–stream system. Changes in diurnal energy inputs alter these pressure cycles with potential ecohydrological consequences.
Martin Beniston, Daniel Farinotti, Markus Stoffel, Liss M. Andreassen, Erika Coppola, Nicolas Eckert, Adriano Fantini, Florie Giacona, Christian Hauck, Matthias Huss, Hendrik Huwald, Michael Lehning, Juan-Ignacio López-Moreno, Jan Magnusson, Christoph Marty, Enrique Morán-Tejéda, Samuel Morin, Mohamed Naaim, Antonello Provenzale, Antoine Rabatel, Delphine Six, Johann Stötter, Ulrich Strasser, Silvia Terzago, and Christian Vincent
The Cryosphere, 12, 759–794, https://doi.org/10.5194/tc-12-759-2018, https://doi.org/10.5194/tc-12-759-2018, 2018
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This paper makes a rather exhaustive overview of current knowledge of past, current, and future aspects of cryospheric issues in continental Europe and makes a number of reflections of areas of uncertainty requiring more attention in both scientific and policy terms. The review paper is completed by a bibliography containing 350 recent references that will certainly be of value to scholars engaged in the fields of glacier, snow, and permafrost research.
Jesús Revuelto, Cesar Azorin-Molina, Esteban Alonso-González, Alba Sanmiguel-Vallelado, Francisco Navarro-Serrano, Ibai Rico, and Juan Ignacio López-Moreno
Earth Syst. Sci. Data, 9, 993–1005, https://doi.org/10.5194/essd-9-993-2017, https://doi.org/10.5194/essd-9-993-2017, 2017
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This work describes the snow and meteorological data set available for the Izas Experimental Catchment in the Central Spanish Pyrenees, from the 2011 to 2017 snow seasons. The climatic data set consists of (i) continuous meteorological variables acquired from an automatic weather station (AWS), (ii) detailed information on snow depth distribution collected with a terrestrial laser scanner for certain dates and (iii) time-lapse images showing the evolution of the snow-covered area.
Jordi Etchanchu, Vincent Rivalland, Simon Gascoin, Jérôme Cros, Tiphaine Tallec, Aurore Brut, and Gilles Boulet
Hydrol. Earth Syst. Sci., 21, 5693–5708, https://doi.org/10.5194/hess-21-5693-2017, https://doi.org/10.5194/hess-21-5693-2017, 2017
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This study assesses the contribution of vegetation dynamics and land use products from high-resolution remote sensing data in the soil–vegetation–atmosphere Transfer ISBA model. We used a field-scale approach (each field is a computation cell) to take advantage of the resolution. The simulations done over an agricultural area in southwestern France showed that integrating such products leads to an improvement of the hydrometeorological fluxes like evapotranspiration or drainage.
Jesús Revuelto, Grégoire Lecourt, Matthieu Lafaysse, Isabella Zin, Luc Charrois, Vincent Vionnet, Marie Dumont, Antoine Rabatel, Delphine Six, Thomas Condom, Samuel Morin, Alessandra Viani, and Pascal Sirguey
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-184, https://doi.org/10.5194/tc-2017-184, 2017
Revised manuscript not accepted
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We evaluated distributed and semi-distributed modeling approaches to simulating the spatial and temporal evolution of snow and ice over an extended mountain catchment, using the Crocus snowpack model. The distributed approach simulated the snowpack dynamics on a 250-m grid, enabling inclusion of terrain shadowing effects. The semi-distributed approach simulated the snowpack dynamics for discrete topographic classes characterized by elevation range, aspect, and slope.
Abbas Fayad, Simon Gascoin, Ghaleb Faour, Pascal Fanise, Laurent Drapeau, Janine Somma, Ali Fadel, Ahmad Al Bitar, and Richard Escadafal
Earth Syst. Sci. Data, 9, 573–587, https://doi.org/10.5194/essd-9-573-2017, https://doi.org/10.5194/essd-9-573-2017, 2017
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Snowmelt plays a key role in the replenishment of the karst groundwater in Lebanon. The proper estimation of the water contained in the snowpack is one of Lebanon's most challenging questions. In this paper, we present continuous meteorological and snow course observations for the first time in the snow-dominated regions of Mount Lebanon. This new dataset can be used to feed an advanced snowpack model and is the first step towards a better evaluation of the snowmelt in Lebanon.
Louise Steffensen Schmidt, Guðfinna Aðalgeirsdóttir, Sverrir Guðmundsson, Peter L. Langen, Finnur Pálsson, Ruth Mottram, Simon Gascoin, and Helgi Björnsson
The Cryosphere, 11, 1665–1684, https://doi.org/10.5194/tc-11-1665-2017, https://doi.org/10.5194/tc-11-1665-2017, 2017
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The regional climate model HIRHAM5 is evaluated over Vatnajökull, Iceland, using automatic weather stations and mass balance observations from 1995 to 2014. From this we asses whether the model can be used to reconstruct the mass balance of the glacier. We find that the simulated energy balance is underestimated overall, but it has been improved by using a new albedo scheme. The specific mass balance is reconstructed back to 1980, thus expanding on the observational records of the mass balance.
Samuel T. Buisán, Michael E. Earle, José Luís Collado, John Kochendorfer, Javier Alastrué, Mareile Wolff, Craig D. Smith, and Juan I. López-Moreno
Atmos. Meas. Tech., 10, 1079–1091, https://doi.org/10.5194/amt-10-1079-2017, https://doi.org/10.5194/amt-10-1079-2017, 2017
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Within the framework of the WMO-SPICE (Solid Precipitation Intercomparison Experiment) the Thies tipping bucket precipitation gauge, widely used at AEMET, was assessed against the SPICE reference.
Most countries use tipping buckets and for this reason the underestimation of snowfall precipitation is a large-scale problem.
The methodology presented here can be used by other national weather services to test precipitation bias corrections and to identify regions where errors are higher.
Melody Sandells, Richard Essery, Nick Rutter, Leanne Wake, Leena Leppänen, and Juha Lemmetyinen
The Cryosphere, 11, 229–246, https://doi.org/10.5194/tc-11-229-2017, https://doi.org/10.5194/tc-11-229-2017, 2017
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This study looks at a wide range of options for simulating sensor signals for satellite monitoring of water stored as snow, though an ensemble of 1323 coupled snow evolution and microwave scattering models. The greatest improvements will be made with better computer simulations of how the snow microstructure changes, followed by how the microstructure scatters radiation at microwave frequencies. Snow compaction should also be considered in systems to monitor snow mass from space.
Paul Hublart, Denis Ruelland, Inaki García de Cortázar-Atauri, Simon Gascoin, Stef Lhermitte, and Antonio Ibacache
Hydrol. Earth Syst. Sci., 20, 3691–3717, https://doi.org/10.5194/hess-20-3691-2016, https://doi.org/10.5194/hess-20-3691-2016, 2016
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Our paper explores the reliability of conceptual catchment models in the dry Andes. First, we show that explicitly accounting for irrigation water use improves streamflow predictions during dry years. Second, we show that sublimation losses can be easily incorporated into temperature-based melt models without increasing model complexity too much. Our work also highlights areas requiring additional research, including the need for a better conceptualization of runoff generation processes.
Graham A. Sexstone, Steven R. Fassnacht, Juan Ignacio López-Moreno, and Christopher A. Hiemstra
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-188, https://doi.org/10.5194/tc-2016-188, 2016
Revised manuscript has not been submitted
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Seasonal snowpacks vary spatially within mountainous environments and the representation of this variability by modeling can be a challenge. This study uses high-resolution airborne lidar data to evaluate the variability of snow depth within a grid size common for modeling applications. Results suggest that snow depth coefficient of variation is well correlated with ecosystem type, depth of snow, and topography and forest characteristics, and can be parameterized using airborne lidar data.
Anita Drumond, Erica Taboada, Raquel Nieto, Luis Gimeno, Sergio M. Vicente-Serrano, and Juan Ignacio López-Moreno
Earth Syst. Dynam., 7, 549–558, https://doi.org/10.5194/esd-7-549-2016, https://doi.org/10.5194/esd-7-549-2016, 2016
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A Lagrangian approach was used to identify the moisture sources for fourteen ice-core sites located worldwide for the present climate. The approach computed budgets of evaporation minus precipitation by calculating changes in the specific humidity along 10-day backward trajectories. The results indicate that the oceanic regions around the subtropical high-pressure centers provide most of moisture, and their contribution varies throughout the year following the annual cycles of the centers.
R. Marti, S. Gascoin, E. Berthier, M. de Pinel, T. Houet, and D. Laffly
The Cryosphere, 10, 1361–1380, https://doi.org/10.5194/tc-10-1361-2016, https://doi.org/10.5194/tc-10-1361-2016, 2016
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To date, there is no definitive approach to map snow depth in mountainous areas from spaceborne sensors. We used very-high-resolution stereo satellites imagery (Pléiades) to generate a map of snow depth in a small Pyrenean catchment. The validation results are promising and open the possibility to retrieve the snow depth at a metric horizontal resolution in remote mountainous areas, even when no field data are available.
Richard Essery, Anna Kontu, Juha Lemmetyinen, Marie Dumont, and Cécile B. Ménard
Geosci. Instrum. Method. Data Syst., 5, 219–227, https://doi.org/10.5194/gi-5-219-2016, https://doi.org/10.5194/gi-5-219-2016, 2016
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Physically based models that predict the properties of snow on the ground are used in many applications, but meteorological input data required by these models are hard to obtain in cold regions. Monitoring at the Sodankyla research station allows construction of model input and evaluation datasets covering several years for the first time in the Arctic. The data are used to show that a sophisticated snow model developed for warmer and wetter sites can perform well in very different conditions.
Juan Ignacio López-Moreno, Jesús Revuelto, Ibai Rico, Javier Chueca-Cía, Asunción Julián, Alfredo Serreta, Enrique Serrano, Sergio Martín Vicente-Serrano, Cesar Azorin-Molina, Esteban Alonso-González, and José María García-Ruiz
The Cryosphere, 10, 681–694, https://doi.org/10.5194/tc-10-681-2016, https://doi.org/10.5194/tc-10-681-2016, 2016
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This paper analyzes the evolution of the Monte Perdido Glacier, Spanish Pyrenees, since 1981. Changes in ice volume were estimated by geodetic methods and terrestrial laser scanning. An acceleration in ice thinning is detected during the 21st century. Local climatic changes observed during the study period do not seem sufficient to explain the acceleration. The strong disequilibrium between the glacier and the current climate and feedback mechanisms seems to be the most plausible explanation.
Sarah S. Thompson, Bernd Kulessa, Richard L. H. Essery, and Martin P. Lüthi
The Cryosphere, 10, 433–444, https://doi.org/10.5194/tc-10-433-2016, https://doi.org/10.5194/tc-10-433-2016, 2016
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We show that strong electrical self-potential fields are generated in melting in in situ snowpacks at Rhone Glacier and Jungfraujoch Glacier, Switzerland. We conclude that the electrical self-potential method is a promising snow and firn hydrology sensor, owing to its suitability for sensing lateral and vertical liquid water flows directly and minimally invasively, complementing established observational programs and monitoring autonomously at a low cost.
R. Essery
Geosci. Model Dev., 8, 3867–3876, https://doi.org/10.5194/gmd-8-3867-2015, https://doi.org/10.5194/gmd-8-3867-2015, 2015
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Models of snow on the ground need to represent processes of solar radiation absorption, heat conduction, liquid water movement and compaction in snow and transfers of heat from the atmosphere. There are many such models in use, but their wide range in complexity makes it hard to understand how differences in process representations determine differences in predictions. Processes in the factorial snow model can be switched on or off independently, allowing highly controlled numerical experiments.
R. Marti, S. Gascoin, T. Houet, O. Ribière, D. Laffly, T. Condom, S. Monnier, M. Schmutz, C. Camerlynck, J. P. Tihay, J. M. Soubeyroux, and P. René
The Cryosphere, 9, 1773–1795, https://doi.org/10.5194/tc-9-1773-2015, https://doi.org/10.5194/tc-9-1773-2015, 2015
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Pyrenean glaciers are currently the southernmost glaciers in Europe. Using an exceptional archive of historical data sets and recent accurate observations, we propose the reconstruction of the length, area, elevation, and mass balance of Ossoue Glacier (French Pyrenees) since the Little Ice Age. We show that its evolution is in good agreement with climatic data. Assuming that the current ablation rate stays constant, Ossoue Glacier will disappear midway through the 21st century.
E. Nadal-Romero, J. Revuelto, P. Errea, and J. I. López-Moreno
SOIL, 1, 561–573, https://doi.org/10.5194/soil-1-561-2015, https://doi.org/10.5194/soil-1-561-2015, 2015
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Geomatic techniques have been routinely applied in erosion studies, providing the opportunity to build high-resolution topographic models.The aim of this study is to assess and compare the functioning of terrestrial laser scanner and close range photogrammetry techniques to evaluate erosion and deposition processes in a humid badlands area.
Our results demonstrated that north slopes experienced more intense and faster dynamics than south slopes as well as the highest erosion rates.
S. E. Chadburn, E. J. Burke, R. L. H. Essery, J. Boike, M. Langer, M. Heikenfeld, P. M. Cox, and P. Friedlingstein
The Cryosphere, 9, 1505–1521, https://doi.org/10.5194/tc-9-1505-2015, https://doi.org/10.5194/tc-9-1505-2015, 2015
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In this paper we use a global land-surface model to study the dynamics of Arctic permafrost. We examine the impact of new and improved processes in the model, namely soil depth and resolution, organic soils, moss and the representation of snow. These improvements make the simulated soil temperatures and thaw depth significantly more realistic. Simulations under future climate scenarios show that permafrost thaws more slowly in the new model version, but still a large amount is lost by 2100.
S. Chadburn, E. Burke, R. Essery, J. Boike, M. Langer, M. Heikenfeld, P. Cox, and P. Friedlingstein
Geosci. Model Dev., 8, 1493–1508, https://doi.org/10.5194/gmd-8-1493-2015, https://doi.org/10.5194/gmd-8-1493-2015, 2015
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Permafrost, ground that is frozen for 2 or more years, is found extensively in the Arctic. It stores large quantities of carbon, which may be released under climate warming, so it is important to include it in climate models. Here we improve the representation of permafrost in a climate model land-surface scheme, both in the numerical representation of soil and snow, and by adding the effects of organic soils and moss. Site simulations show significantly improved soil temperature and thaw depth.
S. Gascoin, O. Hagolle, M. Huc, L. Jarlan, J.-F. Dejoux, C. Szczypta, R. Marti, and R. Sánchez
Hydrol. Earth Syst. Sci., 19, 2337–2351, https://doi.org/10.5194/hess-19-2337-2015, https://doi.org/10.5194/hess-19-2337-2015, 2015
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There is a good agreement between the MODIS snow products and observations from automatic stations and Landsat snow maps in the Pyrenees. The optimal thresholds for which a MODIS pixel is marked as snow-covered are 40mm in water equivalent and 150mm in snow depth.
We generate a gap-filled snow cover climatology for the Pyrenees. We compute the mean snow cover duration by elevation and aspect classes. We show anomalous snow patterns in 2012 and consequences on hydropower production.
S. Ferrant, S. Gascoin, A. Veloso, J. Salmon-Monviola, M. Claverie, V. Rivalland, G. Dedieu, V. Demarez, E. Ceschia, J.-L. Probst, P. Durand, and V. Bustillo
Hydrol. Earth Syst. Sci., 18, 5219–5237, https://doi.org/10.5194/hess-18-5219-2014, https://doi.org/10.5194/hess-18-5219-2014, 2014
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A set of high spatial and temporal satellite images have been used to spatially calibrate crop growth within an agro-hydrological model dedicated to nitrogen contamination of stream water. This type of spatial calibration greatly improved the simulation of nitrogen plant uptake and better constrained nutrient fluxes in the river. This is an example of the benefit of the forthcoming Sentinel-2 high resolution optical image series that will be acquired every 4/5 days over continental surfaces.
J. Revuelto, J. I. López-Moreno, C. Azorin-Molina, and S. M. Vicente-Serrano
The Cryosphere, 8, 1989–2006, https://doi.org/10.5194/tc-8-1989-2014, https://doi.org/10.5194/tc-8-1989-2014, 2014
E. Collier, L. I. Nicholson, B. W. Brock, F. Maussion, R. Essery, and A. B. G. Bush
The Cryosphere, 8, 1429–1444, https://doi.org/10.5194/tc-8-1429-2014, https://doi.org/10.5194/tc-8-1429-2014, 2014
C. B. Ménard, R. Essery, and J. Pomeroy
Hydrol. Earth Syst. Sci., 18, 2375–2392, https://doi.org/10.5194/hess-18-2375-2014, https://doi.org/10.5194/hess-18-2375-2014, 2014
E. Morán-Tejeda, J. Zabalza, K. Rahman, A. Gago-Silva, J. I. López-Moreno, S. Vicente-Serrano, A. Lehmann, C. L. Tague, and M. Beniston
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-11983-2013, https://doi.org/10.5194/hessd-10-11983-2013, 2013
Manuscript not accepted for further review
J. Lorenzo-Lacruz, E. Morán-Tejeda, S. M. Vicente-Serrano, and J. I. López-Moreno
Hydrol. Earth Syst. Sci., 17, 119–134, https://doi.org/10.5194/hess-17-119-2013, https://doi.org/10.5194/hess-17-119-2013, 2013
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Simbi: historical hydro-meteorological time series and signatures for 24 catchments in Haiti
Wangyipu Li, Zhaoyuan Yao, Yifan Qu, Hanbo Yang, Yang Song, Lisheng Song, Lifeng Wu, and Yaokui Cui
Earth Syst. Sci. Data, 17, 3835–3855, https://doi.org/10.5194/essd-17-3835-2025, https://doi.org/10.5194/essd-17-3835-2025, 2025
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Due to shortcomings such as extensive data gaps and limited observation durations in current ground-based latent heat flux (LE) datasets, we developed a novel gap-filling and prolongation framework for ground-based LE observations, establishing a benchmark dataset for global evapotranspiration (ET) estimation from 2000 to 2022 across 64 sites at various timescales. This comprehensive dataset can strongly support ET modeling, water–carbon cycle monitoring, and long-term climate change analysis.
Colleen Mortimer and Vincent Vionnet
Earth Syst. Sci. Data, 17, 3619–3640, https://doi.org/10.5194/essd-17-3619-2025, https://doi.org/10.5194/essd-17-3619-2025, 2025
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In situ observations of snow water equivalent (SWE) are critical for climate applications and resource management. NorSWE is a dataset of in situ SWE observations covering North America, Norway, Finland, Switzerland, Russia, and Nepal over the period 1979–2021. It includes more than 11.5 million observations from more than 10 000 different locations compiled from nine different sources. Snow depth and derived bulk snow density are included when available.
Camille Minaudo, Andras Abonyi, Carles Alcaraz, Jacob Diamond, Nicholas J. K. Howden, Michael Rode, Estela Romero, Vincent Thieu, Fred Worrall, Qian Zhang, and Xavier Benito
Earth Syst. Sci. Data, 17, 3411–3430, https://doi.org/10.5194/essd-17-3411-2025, https://doi.org/10.5194/essd-17-3411-2025, 2025
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Many waterbodies undergo nutrient decline, called oligotrophication, globally, but a comprehensive dataset to understand ecosystem responses is lacking. The OLIGOTREND database comprises multi-decadal chlorophyll a and nutrient time series from rivers, lakes, and estuaries with 4.3 million observations from 1894 unique measurement locations. The database provides empirical evidence for oligotrophication responses with a spatial and temporal coverage that exceeds previous efforts.
Haoxuan Yang, Jia Yang, Tyson E. Ochsner, Erik S. Krueger, Mengyuan Xu, and Chris B. Zou
Earth Syst. Sci. Data, 17, 3391–3409, https://doi.org/10.5194/essd-17-3391-2025, https://doi.org/10.5194/essd-17-3391-2025, 2025
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We developed a 3 h, 1 km surface soil moisture dataset for the contiguous United States from 2015 to 2023 using the spatio-temporal fusion method. This dataset effectively combines the distinct advantages of two long-term surface soil moisture datasets, which is also the first hourly-level 1 km soil moisture dataset at the continental US scale. The new dataset could provide new insight into the fast changes in soil moisture along with drought and wet spell occurrences.
Andrea Galletti, Soroush Zarghami Dastjerdi, and Bruno Majone
Earth Syst. Sci. Data, 17, 3353–3373, https://doi.org/10.5194/essd-17-3353-2025, https://doi.org/10.5194/essd-17-3353-2025, 2025
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IAR-HP (Italian Alpine Region HydroPower) is a detailed inventory of large hydropower systems in Italy's Alpine Region, aimed at improving their inclusion in hydrological modeling by providing relevant information with a consistent level of detail. It includes structural, geographic, and operational data for over 300 hydropower plants and their related reservoirs and water intakes. Validated through modeling, IAR-HP accurately reproduces observed hydropower, capturing 96.2 % of actual production.
Lauranne Alaerts, Jonathan Lambrechts, Ny Riana Randresihaja, Luc Vandenbulcke, Olivier Gourgue, Emmanuel Hanert, and Marilaure Grégoire
Earth Syst. Sci. Data, 17, 3125–3140, https://doi.org/10.5194/essd-17-3125-2025, https://doi.org/10.5194/essd-17-3125-2025, 2025
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We created the first comprehensive, high-resolution, and easily accessible bathymetry dataset for the three main branches of the Danube Delta. By combining four data sources, we obtained a detailed representation of the riverbed, with resolutions ranging from 2 to 100 m. This dataset will support future studies on water and nutrient exchanges between the Danube and the Black Sea and provide insights into the delta's buffer role within the understudied Danube–Black Sea continuum.
Bennett J. McAfee, Aanish Pradhan, Abhilash Neog, Sepideh Fatemi, Robert T. Hensley, Mary E. Lofton, Anuj Karpatne, Cayelan C. Carey, and Paul C. Hanson
Earth Syst. Sci. Data, 17, 3141–3165, https://doi.org/10.5194/essd-17-3141-2025, https://doi.org/10.5194/essd-17-3141-2025, 2025
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LakeBeD-US is a dataset of lake water quality data collected by multiple long-term monitoring programs around the United States. This dataset is designed to foster collaboration between lake scientists and computer scientists to improve predictions of water quality. By offering a way for computer models to be tested against real-world lake data, LakeBeD-US offers opportunities for both sciences to grow and to give new insights into the causes of water quality changes.
Juliette Godet, Pierre Nicolle, Nabil Hocini, Eric Gaume, Philippe Davy, Frederic Pons, Pierre Javelle, Pierre-André Garambois, Dimitri Lague, and Olivier Payrastre
Earth Syst. Sci. Data, 17, 2963–2983, https://doi.org/10.5194/essd-17-2963-2025, https://doi.org/10.5194/essd-17-2963-2025, 2025
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This paper describes a dataset that includes input, output, and validation data for the simulation of flash flood hazards and three specific flash flood events in the French Mediterranean region. This dataset is particularly valuable as flood mapping methods often lack sufficient benchmark data. Additionally, we demonstrate how the hydraulic method we used, named Floodos, produces highly satisfactory results.
Lingbo Li, Hong-Yi Li, Guta Abeshu, Jinyun Tang, L. Ruby Leung, Chang Liao, Zeli Tan, Hanqin Tian, Peter Thornton, and Xiaojuan Yang
Earth Syst. Sci. Data, 17, 2713–2733, https://doi.org/10.5194/essd-17-2713-2025, https://doi.org/10.5194/essd-17-2713-2025, 2025
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We have developed new maps that reveal how organic carbon from soil leaches into headwater streams over the contiguous United States. We use advanced artificial intelligence techniques and a massive amount of data, including observations at over 2500 gauges and a wealth of climate and environmental information. The maps are a critical step in understanding and predicting how carbon moves through our environment, hence making them a useful tool for tackling climate challenges.
Shanti Shwarup Mahto, Simone Fatichi, and Stefano Galelli
Earth Syst. Sci. Data, 17, 2693–2712, https://doi.org/10.5194/essd-17-2693-2025, https://doi.org/10.5194/essd-17-2693-2025, 2025
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The MSEA-Res database offers an open-access dataset tracking absolute water storage for 186 large reservoirs across Mainland Southeast Asia from 1985 to 2023. It provides valuable insights into how reservoir storage grew by 130 % between 2008 and 2017, driven by dams in key river basins. Our data also reveal how droughts, like the 2019–2020 event, significantly impacted water reservoirs. This resource can aid water management, drought planning, and research globally.
Nehar Mandal, Prabal Das, and Kironmala Chanda
Earth Syst. Sci. Data, 17, 2575–2604, https://doi.org/10.5194/essd-17-2575-2025, https://doi.org/10.5194/essd-17-2575-2025, 2025
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Optimal features among hydroclimatic variables and land surface model (LSM) outputs are selected using a novel Bayesian network (BN) approach for simulating terrestrial water storage anomalies (TWSAs). TWSAs are reconstructed (BNML_TWSA) with grid-specific leader models (among four machine learning models) from January 1960 to December 2022 to generate a continuous global gridded dataset. The uncertainty in the reconstructed BNML_TWSA product is also assessed in terms of standard error.
Bernhard Lehner, Mira Anand, Etienne Fluet-Chouinard, Florence Tan, Filipe Aires, George H. Allen, Philippe Bousquet, Josep G. Canadell, Nick Davidson, Meng Ding, C. Max Finlayson, Thomas Gumbricht, Lammert Hilarides, Gustaf Hugelius, Robert B. Jackson, Maartje C. Korver, Liangyun Liu, Peter B. McIntyre, Szabolcs Nagy, David Olefeldt, Tamlin M. Pavelsky, Jean-Francois Pekel, Benjamin Poulter, Catherine Prigent, Jida Wang, Thomas A. Worthington, Dai Yamazaki, Xiao Zhang, and Michele Thieme
Earth Syst. Sci. Data, 17, 2277–2329, https://doi.org/10.5194/essd-17-2277-2025, https://doi.org/10.5194/essd-17-2277-2025, 2025
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The Global Lakes and Wetlands Database (GLWD) version 2 distinguishes a total of 33 non-overlapping wetland classes, providing a static map of the world’s inland surface waters. It contains cell fractions of wetland extents per class at a grid cell resolution of ~500 m. The total combined extent of all classes including all inland and coastal waterbodies and wetlands of all inundation frequencies – that is, the maximum extent – covers 18.2 × 106 km2, equivalent to 13.4 % of total global land area.
Karl Nicolaus van Zweel, Laurent Gourdol, Jean François Iffly, Loïc Léonard, François Barnich, Laurent Pfister, Erwin Zehe, and Christophe Hissler
Earth Syst. Sci. Data, 17, 2217–2229, https://doi.org/10.5194/essd-17-2217-2025, https://doi.org/10.5194/essd-17-2217-2025, 2025
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Our study monitored groundwater in a Luxembourg forest over a year to understand water and chemical changes. We found seasonal variations in water chemistry, influenced by rainfall and soil interactions. These data help predict environmental responses and manage water resources better. By measuring key parameters like pH and dissolved oxygen, our research provides valuable insights into groundwater behaviour and serves as a resource for future environmental studies.
Chang Liao, Darren Engwirda, Matthew G. Cooper, Mingke Li, and Yilin Fang
Earth Syst. Sci. Data, 17, 2035–2062, https://doi.org/10.5194/essd-17-2035-2025, https://doi.org/10.5194/essd-17-2035-2025, 2025
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Discrete global grid systems, or DGGS, are digital frameworks that help us organize information about our planet. Although scientists have used DGGS in areas like weather and nature, using them in the water cycle has been challenging because some core datasets are missing. We created a way to generate these datasets. We then developed the datasets in the Amazon and Yukon basins, which play important roles in our planet's climate. These datasets may help us improve our water cycle models.
Sanchit Minocha and Faisal Hossain
Earth Syst. Sci. Data, 17, 1743–1759, https://doi.org/10.5194/essd-17-1743-2025, https://doi.org/10.5194/essd-17-1743-2025, 2025
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Trustworthy and independently verifiable information on declining storage capacity or sedimentation rates worldwide is sparse and suffers from inconsistent metadata and curation to allow global-scale archiving and analyses. The Global Reservoir Inventory of Lost Storage by Sedimentation (GRILSS) dataset addresses this challenge by providing organized, well-curated, and open-source data on sedimentation rates and capacity loss for 1013 reservoirs in 75 major river basins across 54 countries.
Kimmo Rautiainen, Manu Holmberg, Juval Cohen, Arnaud Mialon, Mike Schwank, Juha Lemmetyinen, Antonio de la Fuente, and Yann Kerr
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-68, https://doi.org/10.5194/essd-2025-68, 2025
Revised manuscript accepted for ESSD
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The SMOS Soil Freeze Thaw State product uses satellite data to monitor seasonal soil freezing and thawing globally, with a focus on high latitude regions. This is important for understanding greenhouse gas emissions, as frozen soil is associated with methane release. The product provides accurate data on key events such as the first day of soil freezing in autumn, helping scientists to study climate change, ecosystem dynamics and its impact on our planet.
Haiguang Cheng, Kaiheng Hu, Shuang Liu, Xiaopeng Zhang, Hao Li, Qiyuan Zhang, Lan Ning, Manish Raj Gouli, Pu Li, Anna Yang, Peng Zhao, Junyu Liu, and Li Wei
Earth Syst. Sci. Data, 17, 1573–1593, https://doi.org/10.5194/essd-17-1573-2025, https://doi.org/10.5194/essd-17-1573-2025, 2025
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After reviewing 2519 literature and media reports, we compiled the first comprehensive global dataset of 555 debris flow barrier dams (DFBDs) from 1800 to 2023. Our dataset meticulously documents 38 attributes of DFBDs, and we have utilized Google Earth for validation. Additionally, we discussed the applicability of landslide dam stability and peak-discharge models to DFBDs. This dataset offers a rich foundation of data for future studies on DFBDs.
Jun Liu, Julian Koch, Simon Stisen, Lars Troldborg, Anker Lajer Højberg, Hans Thodsen, Mark F. T. Hansen, and Raphael J. M. Schneider
Earth Syst. Sci. Data, 17, 1551–1572, https://doi.org/10.5194/essd-17-1551-2025, https://doi.org/10.5194/essd-17-1551-2025, 2025
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We developed a CAMELS-style dataset in Denmark, which contains hydrometeorological time series and landscape attributes for 3330 catchments (304 gauged). Many catchments in CAMELS-DK are small and at low elevations. The dataset provides information on groundwater characteristics and dynamics, as well as quantities related to the human impact on the hydrological system in Denmark. The dataset is especially relevant for developing data-driven and hybrid physically informed modeling frameworks.
Pragnaditya Malakar, Aatish Anshuman, Mukesh Kumar, Georgios Boumis, T. Prabhakar Clement, Arik Tashie, Hitesh Thakur, Nagaraj Bhat, and Lokendra Rathore
Earth Syst. Sci. Data, 17, 1515–1528, https://doi.org/10.5194/essd-17-1515-2025, https://doi.org/10.5194/essd-17-1515-2025, 2025
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Groundwater dynamics depend on groundwater recharge, but daily benchmark data of recharge are scarce. Here we present a daily groundwater recharge per unit specified yield (RpSy) data at 485 US groundwater monitoring wells. RpSy can be used to validate the temporal consistency of recharge products from land surface and hydrologic models and facilitate assessment of recharge-driver functional relationships in them.
Olivier Delaigue, Guilherme Mendoza Guimarães, Pierre Brigode, Benoît Génot, Charles Perrin, Jean-Michel Soubeyroux, Bruno Janet, Nans Addor, and Vazken Andréassian
Earth Syst. Sci. Data, 17, 1461–1479, https://doi.org/10.5194/essd-17-1461-2025, https://doi.org/10.5194/essd-17-1461-2025, 2025
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This dataset covers 654 rivers all flowing in France. The provided time series and catchment attributes will be of interest to those modelers wishing to analyze hydrological behavior and perform model assessments.
Paolo Filippucci, Luca Brocca, Luca Ciabatta, Hamidreza Mosaffa, Francesco Avanzi, and Christian Massari
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-156, https://doi.org/10.5194/essd-2025-156, 2025
Revised manuscript accepted for ESSD
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Accurate rainfall data is essential, yet measuring daily precipitation worldwide is challenging. This research presents HYdroclimatic PERformance-enhanced Precipitation (HYPER-P), a dataset combining satellite, ground, and reanalysis data to estimate precipitation at a 1 km scale from 2000 to 2023. HYPER-P improves accuracy, especially in areas with few rain gauges. This dataset supports scientists and decision-makers in understanding and managing water resources more effectively.
Giulia Evangelista, Paola Mazzoglio, Daniele Ganora, Francesca Pianigiani, and Pierluigi Claps
Earth Syst. Sci. Data, 17, 1407–1426, https://doi.org/10.5194/essd-17-1407-2025, https://doi.org/10.5194/essd-17-1407-2025, 2025
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This paper presents the first comprehensive dataset of 528 large dams in Italy. It contains structural characteristics of the dams, such as coordinates, reservoir surface areas and volumes, together with a range of geomorphological, climatological, extreme rainfall, land cover and soil-related attributes of their upstream catchments.
Jin Feng, Ke Zhang, Lijun Chao, Huijie Zhan, and Yunping Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-137, https://doi.org/10.5194/essd-2025-137, 2025
Revised manuscript accepted for ESSD
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Understanding how soil moisture affects evapotranspiration (ET) is essential for improving ET estimates. However, many global ET datasets overlook soil moisture constraints, causing large uncertainties. In this study, we developed an improved model that better captures the influence of soil moisture on vegetation and soil evaporation. Our model significantly improves ET estimation accuracy and provides a new long-term global ET dataset to support water cycle and climate research.
Yueli Chen, Yun Xie, Xingwu Duan, and Minghu Ding
Earth Syst. Sci. Data, 17, 1265–1274, https://doi.org/10.5194/essd-17-1265-2025, https://doi.org/10.5194/essd-17-1265-2025, 2025
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Rainfall erosivity maps are crucial for identifying key areas of water erosion. Due to the limited historical precipitation data, there are certain biases in rainfall erosivity estimates in China. This study develops a new rainfall erosivity map for mainland China using 1 min precipitation data from 60 129 weather stations, revealing that areas exceeding 4000 MJ mm ha−1 h−1yr−1 of annual rainfall erosivity are mainly concentrated in southern China and on the southern Tibetan Plateau.
Sergey R. Chalov, Victor Ivanov, Danila Shkolnyi, Ekaterina Pavlyukevich, Michal Habel, Dmitry Botavin, Aleksandra Chalova, Pavel Golovlev, Arseny Kamyshev, Roman Kolesnikov, Uliana Koneva, Anna Kurakova, Nadezda Mikhailova, Elizaveta Tuzova, Kristina Prokopeva, Aleksandr Zavadsky, Rituparna Acharyya, Roman S. Chalov, Aleksandr Varenov, Leonid Turykin, Anna Tarbeeva, and Daidu Fan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-150, https://doi.org/10.5194/essd-2025-150, 2025
Revised manuscript accepted for ESSD
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This study presents a unique multi-tool dataset on riverbank migration across Northern Eurasia, covering 140,000 km of river channels over a period of up to 70 years. Using satellite imagery and field observations, we identify key drivers of bank erosion in large spatial scale and highlight role of river discharge and permafrost. The dataset enhances understanding of river channel dynamics and supports the development of predictive models for river channel evolution and erosion risk assessment.
Jan Magnusson, Yves Bühler, Louis Quéno, Bertrand Cluzet, Giulia Mazzotti, Clare Webster, Rebecca Mott, and Tobias Jonas
Earth Syst. Sci. Data, 17, 703–717, https://doi.org/10.5194/essd-17-703-2025, https://doi.org/10.5194/essd-17-703-2025, 2025
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In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land surface, and hydrological models, with potential applications in similar high-alpine catchments.
Nikunj K. Mangukiya, Kanneganti Bhargav Kumar, Pankaj Dey, Shailza Sharma, Vijaykumar Bejagam, Pradeep P. Mujumdar, and Ashutosh Sharma
Earth Syst. Sci. Data, 17, 461–491, https://doi.org/10.5194/essd-17-461-2025, https://doi.org/10.5194/essd-17-461-2025, 2025
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We introduce CAMELS-IND (Catchment Attributes and MEteorology for Large-sample Studies – India), which provides daily hydrometeorological time series and static catchment attributes representing the location, topography, climate, hydrological signatures, land use, land cover, soil, geology, and anthropogenic influences for 472 catchments in Peninsular India to foster large-sample hydrological studies in India and promote the inclusion of Indian catchments in global hydrological research.
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, Cinzia Mazzetti, and Luc Feyen
Earth Syst. Sci. Data, 17, 293–316, https://doi.org/10.5194/essd-17-293-2025, https://doi.org/10.5194/essd-17-293-2025, 2025
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This article presents a reanalysis of Europe's river streamflow for the period 1951–2020. Streamflow is estimated through a state-of-the-art hydrological simulation framework benefitting from detailed information about the landscape, climate, and human activities. The resulting Hydrological European ReAnalysis (HERA) can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources and flood and drought risks.
Daniel Kovacek and Steven Weijs
Earth Syst. Sci. Data, 17, 259–275, https://doi.org/10.5194/essd-17-259-2025, https://doi.org/10.5194/essd-17-259-2025, 2025
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We made a dataset for British Columbia describing the terrain, soil, land cover, and climate of over 1 million watersheds. The attributes are often used in hydrology because they are related to the water cycle. The data are meant to be used for water resources problems that can benefit from lots of watersheds and their attributes. The data and instructions needed to build the dataset from scratch are freely available. The permanent home for the data is https://doi.org/10.5683/SP3/JNKZVT.
Sheng-Lun Tai, Zhao Yang, Brian Gaudet, Koichi Sakaguchi, Larry Berg, Colleen Kaul, Yun Qian, Ye Liu, and Jerome Fast
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-599, https://doi.org/10.5194/essd-2024-599, 2025
Revised manuscript accepted for ESSD
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Our study created a high-resolution soil moisture dataset for the eastern U.S. by integrating satellite data with a land surface model and advanced algorithms, achieving 1-km scale analyses. Validated against multiple networks and datasets, it demonstrated superior accuracy. This dataset is vital for understanding soil moisture dynamics, especially during droughts, and highlights the need for improved modeling of clay soils to refine future predictions.
Yufang Zhang, Shunlin Liang, Han Ma, Tao He, Feng Tian, Guodong Zhang, and Jianglei Xu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-553, https://doi.org/10.5194/essd-2024-553, 2025
Revised manuscript accepted for ESSD
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Soil moisture (SM) plays a vital role in climate, agriculture, and hydrology, yet reliable long-term seamless global datasets remain scarce. To fill this gap, we developed a four-decade seamless global daily 5 km SM product using multi-source datasets and deep learning techniques. This product has long-term coverage, spatial and temporal integrity, and high accuracy, making it a valuable tool for applications like SM trend analysis, drought monitoring, and assessing vegetation responses.
Wolfgang Preimesberger, Pietro Stradiotti, and Wouter Dorigo
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-610, https://doi.org/10.5194/essd-2024-610, 2025
Revised manuscript accepted for ESSD
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We introduce the official ESA CCI Soil Moisture GAPFILLED climate data record. A univariate interpolation algorithm is applied to predict missing data points without relying on ancillary variables. The dataset includes gap-free uncertainty estimates for all predictions and was validated with independent in situ reference measurements. The data are recommended for applications, which require global long-term gap-free satellite soil moisture data.
Bennet Juhls, Anne Morgenstern, Jens Hölemann, Antje Eulenburg, Birgit Heim, Frederieke Miesner, Hendrik Grotheer, Gesine Mollenhauer, Hanno Meyer, Ephraim Erkens, Felica Yara Gehde, Sofia Antonova, Sergey Chalov, Maria Tereshina, Oxana Erina, Evgeniya Fingert, Ekaterina Abramova, Tina Sanders, Liudmila Lebedeva, Nikolai Torgovkin, Georgii Maksimov, Vasily Povazhnyi, Rafael Gonçalves-Araujo, Urban Wünsch, Antonina Chetverova, Sophie Opfergelt, and Pier Paul Overduin
Earth Syst. Sci. Data, 17, 1–28, https://doi.org/10.5194/essd-17-1-2025, https://doi.org/10.5194/essd-17-1-2025, 2025
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The Siberian Arctic is warming fast: permafrost is thawing, river chemistry is changing, and coastal ecosystems are affected. We aimed to understand changes in the Lena River, a major Arctic river flowing to the Arctic Ocean, by collecting 4.5 years of detailed water data, including temperature and carbon and nutrient contents. This dataset records current conditions and helps us to detect future changes. Explore it at https://doi.org/10.1594/PANGAEA.913197 and https://lena-monitoring.awi.de/.
Ralf Loritz, Alexander Dolich, Eduardo Acuña Espinoza, Pia Ebeling, Björn Guse, Jonas Götte, Sibylle K. Hassler, Corina Hauffe, Ingo Heidbüchel, Jens Kiesel, Mirko Mälicke, Hannes Müller-Thomy, Michael Stölzle, and Larisa Tarasova
Earth Syst. Sci. Data, 16, 5625–5642, https://doi.org/10.5194/essd-16-5625-2024, https://doi.org/10.5194/essd-16-5625-2024, 2024
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The CAMELS-DE dataset features data from 1582 streamflow gauges across Germany, with records spanning from 1951 to 2020. This comprehensive dataset, which includes time series of up to 70 years (median 46 years), enables advanced research on water flow and environmental trends and supports the development of hydrological models.
Einara Zahn and Elie Bou-Zeid
Earth Syst. Sci. Data, 16, 5603–5624, https://doi.org/10.5194/essd-16-5603-2024, https://doi.org/10.5194/essd-16-5603-2024, 2024
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Quantifying water and CO2 exchanges through transpiration, evaporation, net photosynthesis, and soil respiration is essential for understanding how ecosystems function. We implemented five methods to estimate these fluxes over a 5-year period across 47 sites. This is the first dataset representing such large spatial and temporal coverage of soil and plant exchanges, and it has many potential applications, such as examining the response of ecosystems to weather extremes and climate change.
Claudia Färber, Henning Plessow, Simon Mischel, Frederik Kratzert, Nans Addor, Guy Shalev, and Ulrich Looser
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-427, https://doi.org/10.5194/essd-2024-427, 2024
Revised manuscript accepted for ESSD
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Large-sample datasets are essential in hydrological science to support modelling studies and advance process understanding. Caravan is a community initiative to create a large-sample hydrology dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world. This dataset is a subset of hydrological discharge data and station-based watersheds from the Global Runoff Data Centre (GRDC), which are covered by an open data policy.
Ling Zhang, Yanhua Xie, Xiufang Zhu, Qimin Ma, and Luca Brocca
Earth Syst. Sci. Data, 16, 5207–5226, https://doi.org/10.5194/essd-16-5207-2024, https://doi.org/10.5194/essd-16-5207-2024, 2024
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This study presented new annual maps of irrigated cropland in China from 2000 to 2020 (CIrrMap250). These maps were developed by integrating remote sensing data, irrigation statistics and surveys, and an irrigation suitability map. CIrrMap250 achieved high accuracy and outperformed currently available products. The new irrigation maps revealed a clear expansion of China’s irrigation area, with the majority (61%) occurring in the water-unsustainable regions facing severe to extreme water stress.
Dominik Paprotny, Paweł Terefenko, and Jakub Śledziowski
Earth Syst. Sci. Data, 16, 5145–5170, https://doi.org/10.5194/essd-16-5145-2024, https://doi.org/10.5194/essd-16-5145-2024, 2024
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Knowledge about past natural disasters can help adaptation to their future occurrences. Here, we present a dataset of 2521 riverine, pluvial, coastal, and compound floods that have occurred in 42 European countries between 1870 and 2020. The dataset contains available information on the inundated area, fatalities, persons affected, or economic loss and was obtained by extensive data collection from more than 800 sources ranging from news reports through government databases to scientific papers.
Paulina Bartkowiak, Bartolomeo Ventura, Alexander Jacob, and Mariapina Castelli
Earth Syst. Sci. Data, 16, 4709–4734, https://doi.org/10.5194/essd-16-4709-2024, https://doi.org/10.5194/essd-16-4709-2024, 2024
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This paper presents the Two-Source Energy Balance evapotranspiration (ET) product driven by Copernicus Sentinel-2 and Sentinel-3 imagery together with ERA5 climate reanalysis data. Daily ET maps are available at 100 m spatial resolution for the period 2017–2021 across four Mediterranean basins: Ebro (Spain), Hérault (France), Medjerda (Tunisia), and Po (Italy). The product is highly beneficial for supporting vegetation monitoring and sustainable water management at the river basin scale.
Fanny J. Sarrazin, Sabine Attinger, and Rohini Kumar
Earth Syst. Sci. Data, 16, 4673–4708, https://doi.org/10.5194/essd-16-4673-2024, https://doi.org/10.5194/essd-16-4673-2024, 2024
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Nitrogen (N) and phosphorus (P) contamination of water bodies is a long-term issue due to the long history of N and P inputs to the environment and their persistence. Here, we introduce a long-term and high-resolution dataset of N and P inputs from wastewater (point sources) for Germany, combining data from different sources and conceptual understanding. We also account for uncertainties in modelling choices, thus facilitating robust long-term and large-scale water quality studies.
Rohit Mukherjee, Frederick Policelli, Ruixue Wang, Elise Arellano-Thompson, Beth Tellman, Prashanti Sharma, Zhijie Zhang, and Jonathan Giezendanner
Earth Syst. Sci. Data, 16, 4311–4323, https://doi.org/10.5194/essd-16-4311-2024, https://doi.org/10.5194/essd-16-4311-2024, 2024
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Global water resource monitoring is crucial due to climate change and population growth. This study presents a hand-labeled dataset of 100 PlanetScope images for surface water detection, spanning diverse biomes. We use this dataset to evaluate two state-of-the-art mapping methods. Results highlight performance variations across biomes, emphasizing the need for diverse, independent validation datasets to enhance the accuracy and reliability of satellite-based surface water monitoring techniques.
Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi
Earth Syst. Sci. Data, 16, 3993–4019, https://doi.org/10.5194/essd-16-3993-2024, https://doi.org/10.5194/essd-16-3993-2024, 2024
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Timely global terrestrial evapotranspiration (ET) data are crucial for water resource management and drought forecasting. This study introduces the VISEA algorithm, which integrates satellite data and shortwave radiation to provide daily 0.05° gridded near-real-time ET estimates. By employing a vegetation index–temperature method, this algorithm can estimate ET without requiring additional data. Evaluation results demonstrate VISEA's comparable accuracy with accelerated data availability.
Sibylle Kathrin Hassler, Rafael Bohn Reckziegel, Ben du Toit, Svenja Hoffmeister, Florian Kestel, Anton Kunneke, Rebekka Maier, and Jonathan Paul Sheppard
Earth Syst. Sci. Data, 16, 3935–3948, https://doi.org/10.5194/essd-16-3935-2024, https://doi.org/10.5194/essd-16-3935-2024, 2024
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Agroforestry systems (AFSs) combine trees and crops within the same land unit, providing a sustainable land use option which protects natural resources and biodiversity. Introducing trees into agricultural systems can positively affect water resources, soil characteristics, biomass and microclimate. We studied an AFS in South Africa in a multidisciplinary approach to assess the different influences and present the resulting dataset consisting of water, soil, tree and meteorological variables.
Keirnan J. A. Fowler, Ziqi Zhang, and Xue Hou
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-263, https://doi.org/10.5194/essd-2024-263, 2024
Revised manuscript accepted for ESSD
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This paper presents Version 2 of the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS v2 comprises data for an increased number (561) of catchments, each with with long-term monitoring, combining hydrometeorological time series with attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. It is freely downloadable from https://zenodo.org/doi/10.5281/zenodo.12575680.
Kaihao Zheng, Peirong Lin, and Ziyun Yin
Earth Syst. Sci. Data, 16, 3873–3891, https://doi.org/10.5194/essd-16-3873-2024, https://doi.org/10.5194/essd-16-3873-2024, 2024
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We develop a globally applicable thresholding scheme for DEM-based floodplain delineation to improve the representation of spatial heterogeneity. It involves a stepwise approach to estimate the basin-level floodplain hydraulic geometry parameters that best respect the scaling law while approximating the global hydrodynamic flood maps. A ~90 m resolution global floodplain map, the Spatial Heterogeneity Improved Floodplain by Terrain analysis (SHIFT), is delineated with demonstrated superiority.
Yuzhong Yang, Qingbai Wu, Xiaoyan Guo, Lu Zhou, Helin Yao, Dandan Zhang, Zhongqiong Zhang, Ji Chen, and Guojun Liu
Earth Syst. Sci. Data, 16, 3755–3770, https://doi.org/10.5194/essd-16-3755-2024, https://doi.org/10.5194/essd-16-3755-2024, 2024
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We present the temporal data of stable isotopes in different waterbodies in the Beiluhe Basin in the hinterland of the Qinghai–Tibet Plateau (QTP) produced between 2017 and 2022. In this article, the first detailed stable isotope data of 359 ground ice samples are presented. This first data set provides a new basis for understanding the hydrological effects of permafrost degradation on the QTP.
Hordur Bragi Helgason and Bart Nijssen
Earth Syst. Sci. Data, 16, 2741–2771, https://doi.org/10.5194/essd-16-2741-2024, https://doi.org/10.5194/essd-16-2741-2024, 2024
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LamaH-Ice is a large-sample hydrology (LSH) dataset for Iceland. The dataset includes daily and hourly hydro-meteorological time series, including observed streamflow and basin characteristics, for 107 basins. LamaH-Ice offers most variables that are included in existing LSH datasets and additional information relevant to cold-region hydrology such as annual time series of glacier extent and mass balance. A large majority of the basins in LamaH-Ice are unaffected by human activities.
Chengcheng Hou, Yan Li, Shan Sang, Xu Zhao, Yanxu Liu, Yinglu Liu, and Fang Zhao
Earth Syst. Sci. Data, 16, 2449–2464, https://doi.org/10.5194/essd-16-2449-2024, https://doi.org/10.5194/essd-16-2449-2024, 2024
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To fill the gap in the gridded industrial water withdrawal (IWW) data in China, we developed the China Industrial Water Withdrawal (CIWW) dataset, which provides monthly IWWs from 1965 to 2020 at a spatial resolution of 0.1°/0.25° and auxiliary data including subsectoral IWW and industrial output value in 2008. This dataset can help understand the human water use dynamics and support studies in hydrology, geography, sustainability sciences, and water resource management and allocation in China.
Pierre-Antoine Versini, Leydy Alejandra Castellanos-Diaz, David Ramier, and Ioulia Tchiguirinskaia
Earth Syst. Sci. Data, 16, 2351–2366, https://doi.org/10.5194/essd-16-2351-2024, https://doi.org/10.5194/essd-16-2351-2024, 2024
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Nature-based solutions (NBSs), such as green roofs, have appeared as relevant solutions to mitigate urban heat islands. The evapotranspiration (ET) process allows NBSs to cool the air. To improve our knowledge about ET assessment, this paper presents some experimental measurement campaigns carried out during three consecutive summers. Data are available for three different (large, small, and point-based) spatial scales.
Ralph Bathelemy, Pierre Brigode, Vazken Andréassian, Charles Perrin, Vincent Moron, Cédric Gaucherel, Emmanuel Tric, and Dominique Boisson
Earth Syst. Sci. Data, 16, 2073–2098, https://doi.org/10.5194/essd-16-2073-2024, https://doi.org/10.5194/essd-16-2073-2024, 2024
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The aim of this work is to provide the first hydroclimatic database for Haiti, a Caribbean country particularly vulnerable to meteorological and hydrological hazards. The resulting database, named Simbi, provides hydroclimatic time series for around 150 stations and 24 catchment areas.
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Short summary
We present a new daily gridded snow depth and snow water equivalent database over the Iberian Peninsula from 1980 to 2014 structured in common elevation bands. The data have proved their consistency with in situ observations and remote sensing data (MODIS). The presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism and risk management.
We present a new daily gridded snow depth and snow water equivalent database over the Iberian...
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