Articles | Volume 22, issue 10
https://doi.org/10.5194/hess-22-5559-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-5559-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Oct 2018
Research article |
| 26 Oct 2018
| 26 Oct 2018
Evaluating and improving modeled turbulent heat fluxes across the North American Great Lakes
Umarporn Charusombat
NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan 48108, USA
University of Michigan, Cooperative Institute for Great Lakes Research, Ann Arbor, Michigan 48108, USA
University of Michigan, Climate & Space Sciences and Engineering Department, Ann Arbor, Michigan 48109, USA
Andrew D. Gronewold
NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan 48108, USA
Brent M. Lofgren
NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan 48108, USA
Eric J. Anderson
NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan 48108, USA
Peter D. Blanken
University of Colorado, Department of Geography, Boulder, Colorado 80309, USA
Christopher Spence
Environment and Climate Change Canada, Saskatoon, Saskatchewan, S7N 5C5, Canada
John D. Lenters
University of Wisconsin-Madison, Center for Limnology, Boulder Junction, Wisconsin 54512, USA
Chuliang Xiao
University of Michigan, Cooperative Institute for Great Lakes Research, Ann Arbor, Michigan 48108, USA
Lindsay E. Fitzpatrick
University of Michigan, Cooperative Institute for Great Lakes Research, Ann Arbor, Michigan 48108, USA
Gregory Cutrell
LimnoTech, Ann Arbor, Michigan 48108, USA
Related authors
No articles found.
Sean P. Burns, Vincent Humphrey, Ethan D. Gutmann, Mark S. Raleigh, David R. Bowling, and Peter D. Blanken
EGUsphere, https://doi.org/10.5194/egusphere-2025-1755, https://doi.org/10.5194/egusphere-2025-1755, 2025
Short summary
Short summary
We compared two techniques that are affected by the amount of liquid water in a forest canopy. One technique relies on remote sensing (a pair of GPS systems) and the other uses tree motion generated by the wind. Though completely different, these two techniques show strikingly similar changes when rain falls on an evergreen forest. We combine these measurements with eddy-covariance fluxes of water vapor to provide some insight into the evaporation of canopy-intercepted precipitation.
Stanley G. Benjamin, Tatiana G. Smirnova, Eric P. James, Eric J. Anderson, Ayumi Fujisaki-Manome, John G. W. Kelley, Greg E. Mann, Andrew D. Gronewold, Philip Chu, and Sean G. T. Kelley
Geosci. Model Dev., 15, 6659–6676, https://doi.org/10.5194/gmd-15-6659-2022, https://doi.org/10.5194/gmd-15-6659-2022, 2022
Short summary
Short summary
Application of 1-D lake models coupled within earth-system prediction models will improve accuracy but requires accurate initialization of lake temperatures. Here, we describe a lake initialization method by cycling within a weather prediction model to constrain lake temperature evolution. We compared these lake temperature values with other estimates and found much reduced errors (down to 1-2 K). The lake cycling initialization is now applied to two operational US NOAA weather models.
Christopher Spence, Zhihua He, Kevin R. Shook, Balew A. Mekonnen, John W. Pomeroy, Colin J. Whitfield, and Jared D. Wolfe
Hydrol. Earth Syst. Sci., 26, 1801–1819, https://doi.org/10.5194/hess-26-1801-2022, https://doi.org/10.5194/hess-26-1801-2022, 2022
Short summary
Short summary
We determined how snow and flow in small creeks change with temperature and precipitation in the Canadian Prairie, a region where water resources are often under stress. We tried something new. Every watershed in the region was placed in one of seven groups based on their landscape traits. We selected one of these groups and used its traits to build a model of snow and streamflow. It worked well, and by the 2040s there may be 20 %–40 % less snow and 30 % less streamflow than the 1980s.
Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu
Biogeosciences, 19, 541–558, https://doi.org/10.5194/bg-19-541-2022, https://doi.org/10.5194/bg-19-541-2022, 2022
Short summary
Short summary
Uncertainty in the response of photosynthesis to temperature poses a major challenge to predicting the response of forests to climate change. In this paper, we study how photosynthesis in a mountainous evergreen forest is limited by temperature. This study highlights that cold temperature is a key factor that controls spring photosynthesis. Including the cold-temperature limitation in an ecosystem model improved its ability to simulate spring photosynthesis.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
Short summary
Short summary
This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Jeffrey M. McKenzie, Barret L. Kurylyk, Michelle A. Walvoord, Victor F. Bense, Daniel Fortier, Christopher Spence, and Christophe Grenier
The Cryosphere, 15, 479–484, https://doi.org/10.5194/tc-15-479-2021, https://doi.org/10.5194/tc-15-479-2021, 2021
Short summary
Short summary
Groundwater is an underappreciated catalyst of environmental change in a warming Arctic. We provide evidence of how changing groundwater systems underpin surface changes in the north, and we argue for research and inclusion of cryohydrogeology, the study of groundwater in cold regions.
Rui Cheng, Troy S. Magney, Debsunder Dutta, David R. Bowling, Barry A. Logan, Sean P. Burns, Peter D. Blanken, Katja Grossmann, Sophia Lopez, Andrew D. Richardson, Jochen Stutz, and Christian Frankenberg
Biogeosciences, 17, 4523–4544, https://doi.org/10.5194/bg-17-4523-2020, https://doi.org/10.5194/bg-17-4523-2020, 2020
Short summary
Short summary
We measured reflected sunlight from an evergreen canopy for a year to detect changes in pigments that play an important role in regulating the seasonality of photosynthesis. Results show a strong mechanistic link between spectral reflectance features and pigment content, which is validated using a biophysical model. Our results show spectrally where, why, and when spectral features change over the course of the season and show promise for estimating photosynthesis remotely.
Nicholas C. Parazoo, Troy Magney, Alex Norton, Brett Raczka, Cédric Bacour, Fabienne Maignan, Ian Baker, Yongguang Zhang, Bo Qiu, Mingjie Shi, Natasha MacBean, Dave R. Bowling, Sean P. Burns, Peter D. Blanken, Jochen Stutz, Katja Grossmann, and Christian Frankenberg
Biogeosciences, 17, 3733–3755, https://doi.org/10.5194/bg-17-3733-2020, https://doi.org/10.5194/bg-17-3733-2020, 2020
Short summary
Short summary
Satellite measurements of solar-induced chlorophyll fluorescence (SIF) provide a global measure of photosynthetic change. This enables scientists to better track carbon cycle responses to environmental change and tune biochemical processes in vegetation models for an improved simulation of future change. We use tower-instrumented SIF measurements and controlled model experiments to assess the state of the art in terrestrial biosphere SIF modeling and find a wide range of sensitivities to light.
Jared D. Wolfe, Kevin R. Shook, Chris Spence, and Colin J. Whitfield
Hydrol. Earth Syst. Sci., 23, 3945–3967, https://doi.org/10.5194/hess-23-3945-2019, https://doi.org/10.5194/hess-23-3945-2019, 2019
Short summary
Short summary
Watershed classification can identify regions expected to respond similarly to disturbance. Methods should extend beyond hydrology to include other environmental questions, such as ecology and water quality. We developed a classification for the Canadian Prairie and identified seven classes defined by watershed characteristics, including elevation, climate, wetland density, and surficial geology. Results provide a basis for evaluating watershed response to land management and climate condition.
Edward K. P. Bam, Rosa Brannen, Sujata Budhathoki, Andrew M. Ireson, Chris Spence, and Garth van der Kamp
Earth Syst. Sci. Data, 11, 553–563, https://doi.org/10.5194/essd-11-553-2019, https://doi.org/10.5194/essd-11-553-2019, 2019
Short summary
Short summary
The paper highlights the data contained in the database for the Prairie research site, St. Denis National Wildlife Research Area, at Saskatchewan, Canada. The database includes atmosphere, snow surveys, pond, soil, groundwater, and water isotopes collected on an intermittent basis between 1968 and 2018. The metadata table provides location information, information about the full range of measurements carried out on each parameter, and GPS locations relevant for interpretation of the data.
Christopher Spence and Newell Hedstrom
Earth Syst. Sci. Data, 10, 1753–1767, https://doi.org/10.5194/essd-10-1753-2018, https://doi.org/10.5194/essd-10-1753-2018, 2018
Short summary
Short summary
This dataset documents physiographic and hydrometeorological conditions from 2003 to 2016 in the 155 km2 Baker Creek Research Watershed in Canada's Northwest Territories. Half-hourly hydrometeorological data were collected over several land cover types. The dataset includes streamflow, ground temperature, soil moisture, and spring maximum snow depth and water content. These data are unique in this remote region and provide scientific and engineering communities data to advance understanding.
Katheryn Burd, Suzanne E. Tank, Nicole Dion, William L. Quinton, Christopher Spence, Andrew J. Tanentzap, and David Olefeldt
Hydrol. Earth Syst. Sci., 22, 4455–4472, https://doi.org/10.5194/hess-22-4455-2018, https://doi.org/10.5194/hess-22-4455-2018, 2018
Short summary
Short summary
In this study we investigated whether climate change and wildfires are likely to alter water quality of streams in western boreal Canada, a region that contains large permafrost-affected peatlands. We monitored stream discharge and water quality from early snowmelt to fall in two streams, one of which drained a recently burned landscape. Wildfire increased the stream delivery of phosphorous and possibly increased the release of old natural organic matter previously stored in permafrost soils.
José-Luis Guerrero, Patricia Pernica, Howard Wheater, Murray Mackay, and Chris Spence
Hydrol. Earth Syst. Sci., 21, 6345–6362, https://doi.org/10.5194/hess-21-6345-2017, https://doi.org/10.5194/hess-21-6345-2017, 2017
Short summary
Short summary
Lakes are sentinels of climate change, and an adequate characterization of their feedbacks to the atmosphere could improve climate modeling. These feedbacks, as heat fluxes, can be simulated but are seldom measured, casting doubt on modeling results. Measurements from a small lake in Canada established that the model parameter modulating how much light penetrates the lake dominates model response. This parameter is measurable: improved monitoring could lead to more robust modeling.
Étienne Gaborit, Vincent Fortin, Xiaoyong Xu, Frank Seglenieks, Bryan Tolson, Lauren M. Fry, Tim Hunter, François Anctil, and Andrew D. Gronewold
Hydrol. Earth Syst. Sci., 21, 4825–4839, https://doi.org/10.5194/hess-21-4825-2017, https://doi.org/10.5194/hess-21-4825-2017, 2017
Short summary
Short summary
The work presents an original methodology for optimizing streamflow simulations with the distributed hydrological model GEM-Hydro.
While minimizing the computational time required for automatic calibration, the approach allows us to end up with a spatially coherent and transferable parameter set. The GEM-Hydro model is useful because it allows simulation of all physical components of the hydrological cycle in every part of a domain.
It proves to be competitive with other distributed models.
Francesc Montané, Andrew M. Fox, Avelino F. Arellano, Natasha MacBean, M. Ross Alexander, Alex Dye, Daniel A. Bishop, Valerie Trouet, Flurin Babst, Amy E. Hessl, Neil Pederson, Peter D. Blanken, Gil Bohrer, Christopher M. Gough, Marcy E. Litvak, Kimberly A. Novick, Richard P. Phillips, Jeffrey D. Wood, and David J. P. Moore
Geosci. Model Dev., 10, 3499–3517, https://doi.org/10.5194/gmd-10-3499-2017, https://doi.org/10.5194/gmd-10-3499-2017, 2017
Short summary
Short summary
How carbon is allocated to different plant tissues (leaves, stem, and roots) determines carbon residence time and thus remains a central challenge for understanding the global carbon cycle. In this paper, we compared standard and novel carbon allocation schemes in CLM4.5 and evaluated them using eddy covariance wood and leaf biomass. The dynamic scheme based on work by Litton improved model performance, but this was dependent on model assumptions about woody turnover.
Christopher Spence and Samson Girma Mengistu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-252, https://doi.org/10.5194/hess-2017-252, 2017
Manuscript not accepted for further review
Short summary
Short summary
This research summarizes the application of a hydrological model to determine the relationships between streamflow and the area that contributes water to it. The model performed well. Results show that the frequency of streamflow events and with which areas contribute are not necessarily the same. There are implications from this research for determining the sources of water and nutrients available downstream in lakes vulnerable to eutrophication.
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
The role of land–atmosphere coupling in subseasonal surface air temperature prediction across the contiguous United States
Barriers to urban hydrometeorological simulation: a review
Global catalog of soil moisture droughts over the past four decades
Probabilistic precipitation downscaling for ungauged mountain sites: a pilot study for the Hindu Kush Himalaya
Implementation of global soil databases in the Noah-MP model and the effects on simulated mean and extreme soil hydrothermal changes
Skilful probabilistic predictions of UK flood risk months ahead using a large-sample machine learning model trained on multimodel ensemble climate forecasts
Towards a robust hydrologic data assimilation system for hurricane-induced river flow forecasting
Enhanced evaluation of hourly and daily extreme precipitation in Norway from convection-permitting models at regional and local scales
Deep-learning-based sub-seasonal precipitation and streamflow ensemble forecasting over the source region of the Yangtze River
High-resolution land surface modelling over Africa: the role of uncertain soil properties in combination with forcing temporal resolution
Investigating the global and regional response of drought to idealized deforestation using multiple global climate models
Distribution, trends, and drivers of flash droughts in the United Kingdom
Are dependencies of extreme rainfall on humidity more reliable in convection-permitting climate models?
Leveraging a radar-based disdrometer network to develop a probabilistic precipitation phase model in eastern Canada
Assessment of seasonal soil moisture forecasts over the Central Mediterranean
Saudi Rainfall (SaRa): Hourly 0.1° Gridded Rainfall (1979–Present) for Saudi Arabia via Machine Learning Fusion of Satellite and Model Data
Do land models miss key soil hydrological processes controlling soil moisture memory?
Observation-driven model for calculating water-harvesting potential from advective fog in (semi-)arid coastal regions
Review of gridded climate products and their use in hydrological analyses reveals overlaps, gaps, and the need for a more objective approach to selecting model forcing datasets
Downscaling the probability of heavy rainfall over the Nordic countries
Modelling convective cell life cycles with a copula-based approach
Downscaling precipitation over High-mountain Asia using multi-fidelity Gaussian processes: improved estimates from ERA5
Mapping soil moisture across the UK: assimilating cosmic-ray neutron sensors, remotely sensed indices, rainfall radar and catchment water balance data in a Bayesian hierarchical model
Informativeness of teleconnections in local and regional frequency analysis of rainfall extremes
Assessing rainfall radar errors with an inverse stochastic modelling framework
Enhanced hydrological modelling with the WRF-Hydro lake/reservoir module at Convection-Permitting scale: a case study of the Tana River basin in East Africa
Multi-objective calibration and evaluation of the ORCHIDEE land surface model over France at high resolution
Spatiotemporal responses of runoff to climate change in the southern Tibetan Plateau
FROSTBYTE: a reproducible data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America
Storyline Analytical Framework for Understanding Future Severe Low-Water Episodes and Their Consequences
Assessing multivariate bias corrections of climate simulations on various impact models under climate change
On the combined use of rain gauges and GPM IMERG satellite rainfall products for hydrological modelling: impact assessment of the cellular-automata-based methodology in the Tanaro River basin in Italy
An increase in the spatial extent of European floods over the last 70 years
140-year daily ensemble streamflow reconstructions over 661 catchments in France
The agricultural expansion in South America's Dry Chaco: regional hydroclimate effects
Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China
Improving runoff simulation in the Western United States with Noah-MP and VIC models
Spatial variability in the seasonal precipitation lapse rates in complex topographical regions – application in France
Assessing downscaling methods to simulate hydrologically relevant weather scenarios from a global atmospheric reanalysis: case study of the upper Rhône River (1902–2009)
Global total precipitable water variations and trends over the period 1958–2021
Assessing decadal- to centennial-scale nonstationary variability in meteorological drought trends
Identification of compound drought and heatwave events on a daily scale and across four seasons
Potential for historically unprecedented Australian droughts from natural variability and climate change
Flood risk assessment for Indian sub-continental river basins
Key ingredients in regional climate modelling for improving the representation of typhoon tracks and intensities
Divergent future drought projections in UK river flows and groundwater levels
Predicting extreme sub-hourly precipitation intensification based on temperature shifts
Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments
Accounting for hydroclimatic properties in flood frequency analysis procedures
Understanding the influence of “hot” models in climate impact studies: a hydrological perspective
Yuna Lim, Andrea M. Molod, Randal D. Koster, and Joseph A. Santanello
Hydrol. Earth Syst. Sci., 29, 3435–3445, https://doi.org/10.5194/hess-29-3435-2025, https://doi.org/10.5194/hess-29-3435-2025, 2025
Short summary
Short summary
To better utilize a given set of predictions, identifying “forecasts of opportunity” is valuable as this helps anticipate when prediction skill will be higher. This study shows that when strong land–atmosphere (L–A) coupling is detected 3–4 weeks into a forecast, the surface air temperature prediction skill at this lead time increases across the Midwest and northern Great Plains. Regions experiencing strong L–A coupling exhibit warm and dry anomalies, enhancing predictions of abnormally warm events.
Xuan Chen, Job Augustijn van der Werf, Arjan Droste, Miriam Coenders-Gerrits, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 29, 3447–3480, https://doi.org/10.5194/hess-29-3447-2025, https://doi.org/10.5194/hess-29-3447-2025, 2025
Short summary
Short summary
The review highlights the need to integrate urban land surface and hydrological models to better predict and manage compound climate events in cities. We find that inadequate representation of water surfaces, hydraulic systems and detailed building representations are key areas for improvement in future models. Coupled models show promise but face challenges at regional and neighbourhood scales. Interdisciplinary communication is crucial to enhance urban hydrometeorological simulations.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, Yannis Markonis, and Miroslav Trnka
Hydrol. Earth Syst. Sci., 29, 3341–3358, https://doi.org/10.5194/hess-29-3341-2025, https://doi.org/10.5194/hess-29-3341-2025, 2025
Short summary
Short summary
We present a robust method for identification and classification of global land drought events (GLDEs) based on soil moisture. Two models were used to calculate soil moisture and delimit soil drought over global land from 1980–2022, with clusters of 775 and 630 GLDEs. Using four spatiotemporal and three motion-related characteristics, we categorized GLDEs into seven severity and seven dynamic categories. The frequency of GLDEs has generally increased in recent decades.
Marc Girona-Mata, Andrew Orr, Martin Widmann, Daniel Bannister, Ghulam Hussain Dars, Scott Hosking, Jesse Norris, David Ocio, Tony Phillips, Jakob Steiner, and Richard E. Turner
Hydrol. Earth Syst. Sci., 29, 3073–3100, https://doi.org/10.5194/hess-29-3073-2025, https://doi.org/10.5194/hess-29-3073-2025, 2025
Short summary
Short summary
We introduce a novel method for improving daily precipitation maps in mountain regions and pilot it across three basins in the Hindu Kush Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical or machine learning techniques. Our results show that this approach outperforms traditional methods, especially in remote ungauged areas, suggesting that it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
Kazeem Abiodun Ishola, Gerald Mills, Ankur Prabhat Sati, Benjamin Obe, Matthias Demuzere, Deepak Upreti, Gourav Misra, Paul Lewis, Daire Walsh, Tim McCarthy, and Rowan Fealy
Hydrol. Earth Syst. Sci., 29, 2551–2582, https://doi.org/10.5194/hess-29-2551-2025, https://doi.org/10.5194/hess-29-2551-2025, 2025
Short summary
Short summary
Global soil information introduces uncertainty into models that simulate soil hydrothermal changes. Using the Noah with Multiparameterization (Noah-MP) model with two different global soil datasets, we find under-represented soil properties in wet loam, causing a dry bias in soil moisture. This bias is more pronounced and drought categories are more severe in the SoilGrids dataset. We conclude that models should incorporate detailed, region-specific soil information to minimize model uncertainties.
Simon Moulds, Louise Slater, Louise Arnal, and Andrew W. Wood
Hydrol. Earth Syst. Sci., 29, 2393–2406, https://doi.org/10.5194/hess-29-2393-2025, https://doi.org/10.5194/hess-29-2393-2025, 2025
Short summary
Short summary
Seasonal streamflow forecasts are an important component of flood risk management. Here, we train and test a machine learning model to predict the monthly maximum daily streamflow up to 4 months ahead. We train the model on precipitation and temperature forecasts to produce probabilistic hindcasts for 579 stations across the UK for the period 2004–2016. We show skilful results up to 4 months ahead in many locations, although, in general, the skill declines with increasing lead time.
Peyman Abbaszadeh, Fatemeh Gholizadeh, Keyhan Gavahi, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 29, 2407–2427, https://doi.org/10.5194/hess-29-2407-2025, https://doi.org/10.5194/hess-29-2407-2025, 2025
Short summary
Short summary
The Hybrid Ensemble and Variational Data Assimilation framework for Environmental Systems (HEAVEN) enhances flood predictions by refining hydrologic models through improved data integration and uncertainty management. Tested in three southeastern US watersheds during hurricanes, HEAVEN assimilates real-time United States Geological Survey (USGS) streamflow data, boosting forecast accuracy.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Göktürk
Hydrol. Earth Syst. Sci., 29, 2133–2152, https://doi.org/10.5194/hess-29-2133-2025, https://doi.org/10.5194/hess-29-2133-2025, 2025
Short summary
Short summary
We compared hourly and daily extreme precipitation across Norway from HARMONIE Climate models at convection-permitting 3 km (HCLIM3) and 12 km (HCLIM12) resolutions. HCLIM3 more accurately captures the extremes in most regions and seasons (except in summer). Its advantages are more pronounced for hourly extremes than for daily extremes. The results highlight the value of convection-permitting models in improving extreme-precipitation predictions and in helping the local society brace for extreme weather.
Ningpeng Dong, Haoran Hao, Mingxiang Yang, Jianhui Wei, Shiqin Xu, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 29, 2023–2042, https://doi.org/10.5194/hess-29-2023-2025, https://doi.org/10.5194/hess-29-2023-2025, 2025
Short summary
Short summary
Hydrometeorological forecasting is crucial for managing water resources and mitigating extreme weather events, yet current long-term forecast products are often embedded with uncertainties. We develop a deep-learning-based modelling framework to improve 30 d rainfall and streamflow forecasts by combining advanced neural networks and physical models. With the flow forecast error reduced by up to 33 %, the framework has the potential to enhance water management and disaster prevention.
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025, https://doi.org/10.5194/hess-29-1659-2025, 2025
Short summary
Short summary
We studied how soil and weather data affect land model simulations over Africa. By combining soil data processed in different ways with weather data of varying time intervals, we found that weather inputs had a greater impact on water processes than soil data type. However, the way soil data were processed became crucial when paired with high-frequency weather inputs, showing that detailed weather data can improve local and regional predictions of how water moves and interacts with the land.
Yan Li, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust
Hydrol. Earth Syst. Sci., 29, 1637–1658, https://doi.org/10.5194/hess-29-1637-2025, https://doi.org/10.5194/hess-29-1637-2025, 2025
Short summary
Short summary
Deforestation has a significant impact on climate, yet its effects on drought remain less understood. This study investigates how deforestation affects drought across various climate zones and timescales. Findings indicate that deforestation leads to drier conditions in tropical regions and wetter conditions in arid areas, with minimal effects in temperate zones. Long-term drought is more affected than short-term drought, offering valuable insights into vegetation–climate interactions.
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 29, 1295–1317, https://doi.org/10.5194/hess-29-1295-2025, https://doi.org/10.5194/hess-29-1295-2025, 2025
Short summary
Short summary
The study provides a detailed characterisation of flash drought in the UK for 1969–2021. The spatio-temporal distribution and trends of flash droughts are highly variable, with important regional and seasonal contrasts. In the UK, flash drought development responds primarily to precipitation variability, while the atmospheric evaporative demand plays a secondary role. We also found that the North Atlantic Oscillation is the main circulation pattern controlling flash drought development.
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley J. Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci., 29, 1201–1220, https://doi.org/10.5194/hess-29-1201-2025, https://doi.org/10.5194/hess-29-1201-2025, 2025
Short summary
Short summary
Future extreme rainfall events are influenced by changes in both absolute and relative humidity. The impact of increasing absolute humidity is reasonably well understood, but the role of relative humidity decreases over land remains largely unknown. Using hourly observations from France and the Netherlands, we find that lower relative humidity generally leads to more intense rainfall extremes. This relation is only captured well in recently developed convection-permitting climate models.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci., 29, 1135–1158, https://doi.org/10.5194/hess-29-1135-2025, https://doi.org/10.5194/hess-29-1135-2025, 2025
Short summary
Short summary
Precipitation data from an automated observational network in eastern Canada showed a temperature interval where rain and snow could coexist. Random forest models were developed to classify the precipitation phase using meteorological data to evaluate operational applications. The models demonstrated significantly improved phase classification and reduced error compared to benchmark operational models. However, accurate prediction of mixed-phase precipitation remains challenging.
Lorenzo Silvestri, Miriam Saraceni, Bruno Brunone, Silvia Meniconi, Giulia Passadore, and Paolina Bongioannini Cerlini
Hydrol. Earth Syst. Sci., 29, 925–946, https://doi.org/10.5194/hess-29-925-2025, https://doi.org/10.5194/hess-29-925-2025, 2025
Short summary
Short summary
This work demonstrates that seasonal forecasts of soil moisture are a valuable resource for groundwater management in the areas of the Central Mediterranean where longer memory timescales are found. In particular, they show significant correlation coefficients and forecast skill for the deepest soil moisture at 289 cm depth. Wet and dry events can be predicted 6 months in advance, and, in general, dry events are better captured than wet events.
Xuetong Wang, Raied S. Alharbi, Oscar M. Baez-Villanueva, Amy Green, Matthew F. McCabe, Yoshihide Wada, Albert I. J. M. Van Dijk, Muhammad A. Abid, and Hylke Beck
EGUsphere, https://doi.org/10.5194/egusphere-2025-254, https://doi.org/10.5194/egusphere-2025-254, 2025
Short summary
Short summary
Our paper introduces Saudi Rainfall (SaRa), a high-resolution, near real-time rainfall product for the Arabian Peninsula. Using machine learning, SaRa combines multiple satellite and (re)analysis datasets with static predictors, outperforming existing products in the region. With the fast development and continuing growth in water demand over this region, SaRa could help to address water challenges and support resource management.
Mohammad A. Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
Hydrol. Earth Syst. Sci., 29, 547–566, https://doi.org/10.5194/hess-29-547-2025, https://doi.org/10.5194/hess-29-547-2025, 2025
Short summary
Short summary
Soil moisture memory (SMM) shows how long soil stays moist after rain, impacting climate and ecosystems. Current models often overestimate SMM, causing inaccuracies in evaporation predictions. We enhanced a land model, Noah-MP, to include better water flow and ponding processes, and we tested it against satellite and field data. This improved model reduced overestimations and enhanced short-term predictions, helping create more accurate climate and weather forecasts.
Felipe Lobos-Roco, Jordi Vilà-Guerau de Arellano, and Camilo del Río
Hydrol. Earth Syst. Sci., 29, 109–125, https://doi.org/10.5194/hess-29-109-2025, https://doi.org/10.5194/hess-29-109-2025, 2025
Short summary
Short summary
Water resources are fundamental for the social, economic, and natural development of (semi-)arid regions. Precipitation decreases due to climate change obligate us to find new water resources. Fog harvesting (FH) emerges as a complementary resource in regions where it is abundant but untapped. This research proposes a model to estimate FH potential in coastal (semi-)arid regions. This model could have broader applicability worldwide in regions where FH could be a viable water source.
Kyle R. Mankin, Sushant Mehan, Timothy R. Green, and David M. Barnard
Hydrol. Earth Syst. Sci., 29, 85–108, https://doi.org/10.5194/hess-29-85-2025, https://doi.org/10.5194/hess-29-85-2025, 2025
Short summary
Short summary
We assess 63 gridded ground (G), satellite (S), and reanalysis (R) climate datasets. Higher-density station data and less-hilly terrain improved climate data. In mountainous and humid regions, dataset types performed similarly; however, R outperformed G when underlying data had low station density. G outperformed S or R datasets, although better streamflow modeling did not always follow. Hydrologic analyses need datasets that better represent climate variable dependencies and complex topography.
Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
Hydrol. Earth Syst. Sci., 29, 45–65, https://doi.org/10.5194/hess-29-45-2025, https://doi.org/10.5194/hess-29-45-2025, 2025
Short summary
Short summary
We present a new method to calculate the chance of heavy downpour and the maximum rainfall expected over a 25-year period. It is designed to analyse global climate models' reproduction of past and future climates. For the Nordic countries, it projects a wetter climate in the future with increased intensity but not necessarily more wet days. The analysis also shows that rainfall intensity is sensitive to future greenhouse gas emissions, while the number of wet days appears to be less affected.
Chien-Yu Tseng, Li-Pen Wang, and Christian Onof
Hydrol. Earth Syst. Sci., 29, 1–25, https://doi.org/10.5194/hess-29-1-2025, https://doi.org/10.5194/hess-29-1-2025, 2025
Short summary
Short summary
This study presents a new algorithm to model convective storms. We used advanced tracking methods to analyse 165 storm events in Birmingham (UK) and reconstruct storm cell life cycles. We found that cell properties like intensity and size are interrelated and vary over time. The new algorithm, based on vine copulas, accurately simulates these properties and their evolution. It also integrates an exponential shape function for realistic rainfall patterns, enhancing its hydrological applicability.
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024, https://doi.org/10.5194/hess-28-4903-2024, 2024
Short summary
Short summary
This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions, including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows accuracy comparable to or better than existing benchmark datasets.
Peter E. Levy and the COSMOS-UK team
Hydrol. Earth Syst. Sci., 28, 4819–4836, https://doi.org/10.5194/hess-28-4819-2024, https://doi.org/10.5194/hess-28-4819-2024, 2024
Short summary
Short summary
Having accurate up-to-date maps of soil moisture is important for many purposes. However, current modelled and remotely sensed maps are rather coarse and not very accurate. Here, we demonstrate a simple but accurate approach that is closely linked to direct measurements of soil moisture at a network sites across the UK, to the water balance (precipitation minus drainage and evaporation) measured at a large number of catchments (1212) and to remotely sensed satellite estimates.
Andrea Magnini, Valentina Pavan, and Attilio Castellarin
EGUsphere, https://doi.org/10.5194/egusphere-2024-3261, https://doi.org/10.5194/egusphere-2024-3261, 2024
Short summary
Short summary
This study describes a new methodology to identify regional structures in the dependence of extreme rainfall on global climate indexes. The study area is north-central Italy, but the methods are highly adaptable to other regions. We observe that the Western Mediterranean Oscillation Index has a strong influence, whose geographical pattern is in line with other studies. We show also that the use of the Index may improve the estimation of the extreme rainfall depth with a given probability.
Amy C. Green, Chris Kilsby, and András Bárdossy
Hydrol. Earth Syst. Sci., 28, 4539–4558, https://doi.org/10.5194/hess-28-4539-2024, https://doi.org/10.5194/hess-28-4539-2024, 2024
Short summary
Short summary
Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well in generating realistic weather radar images visually for a large range of event types.
Ling Zhang, Lu Li, Zhongshi Zhang, Joël Arnault, Stefan Sobolowski, Anthony Musili Mwanthi, Pratik Kad, Mohammed Abdullahi Hassan, Tanja Portele, and Harald Kunstmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-278, https://doi.org/10.5194/hess-2024-278, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
To address challenges related to unreliable hydrological simulations, we present an enhanced hydrological simulation with a refined climate model and a more comprehensive hydrological model. The model with the two parts outperforms that without, especially in migrating bias in peak flow and dry-season flow. Our findings highlight the enhanced hydrological simulation capability with the refined climate and lake module contributing 24 % and 76 % improvement, respectively.
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
Hydrol. Earth Syst. Sci., 28, 4455–4476, https://doi.org/10.5194/hess-28-4455-2024, https://doi.org/10.5194/hess-28-4455-2024, 2024
Short summary
Short summary
We conducted a high-resolution hydrological simulation from 1959 to 2020 across France. We used a simple trial-and-error calibration to reduce the biases of the simulated water budget compared to observations. The selected simulation satisfactorily reproduces water fluxes, including their spatial contrasts and temporal trends. This work offers a reliable historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
Short summary
Short summary
Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
Short summary
Short summary
Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Gabriel Rondeau-Genesse, Louis-Philippe Caron, Kristelle Audet, Laurent Da Silva, Daniel Tarte, Rachel Parent, Élise Comeau, and Dominic Matte
EGUsphere, https://doi.org/10.5194/egusphere-2024-2595, https://doi.org/10.5194/egusphere-2024-2595, 2024
Short summary
Short summary
The 2021 drought in Quebec showcased the province’s potential vulnerability. This study uses a storyline approach to explore impacts of future extreme droughts under +2 °C and +3 °C warming scenarios. By combining regional climate and hydrological simulations, it highlights the potential for severe water deficits. Collaboration with water management experts helped project the impacts of those future extreme droughts and their consequences for ecosystems and human activities.
Denis Allard, Mathieu Vrac, Bastien François, and Iñaki García de Cortázar-Atauri
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-102, https://doi.org/10.5194/hess-2024-102, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Atmospheric variables from climate models often present biases relative to the past. In order to use these models to assess the impact of climate change on processes of interest, it is necessary to correct these biases. We tested several Multivariate Bias Correction Methods (MBCMs) for 5 physical variables that are input variables for 4 process models. We provide recommendations regarding the use of MBCMs when multivariate and time dependent processes are involved.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
Short summary
Short summary
The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
Short summary
Short summary
We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
Short summary
Short summary
Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
Short summary
Short summary
The Gran Chaco is a large, dry forest in South America that has been heavily deforested, particularly in the dry Chaco subregion. This deforestation, mainly driven by the expansion of the agricultural frontier, has changed the land's characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
Short summary
Short summary
Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
Short summary
Short summary
We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
Short summary
Short summary
The increase in precipitation as a function of elevation is poorly understood in areas with complex topography. In this article, the reproduction of these orographic gradients is assessed with several precipitation products. The best product is a simulation from a convection-permitting regional climate model. The corresponding seasonal gradients vary significantly in space, with higher values for the first topographical barriers exposed to the dominant air mass circulations.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
Short summary
Short summary
Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
Short summary
Short summary
Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
Short summary
Short summary
This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
Short summary
Short summary
This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
Short summary
Short summary
Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
Short summary
Short summary
A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
Short summary
Short summary
Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
Short summary
Short summary
We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
Short summary
Short summary
We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
Short summary
Short summary
Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
Short summary
Short summary
Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
Short summary
Short summary
Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Cited articles
Anderson, E. J. and Schwab, D. J.: Predicting the oscillating bi-directional
exchange flow in the Straits of Mackinac, J. Great Lakes Res., 39, 663–671,
https://doi.org/10.1016/j.jglr.2013.09.001, 2013.
Anderson, E. J., Bechle, A. J., Wu, C. H., Schwab, D. J., Mann, G. E., and
Lombardy, K. A.: Reconstruction of a meteotsunami in Lake Erie on 27 May 2012;
Roles of atmospheric conditions on hydrodynamic response in enclosed basins,
J. Geophys. Res., 120, 1–16, https://doi.org/10.1002/2014JC010564, 2015.
Andreas, E. L.: A theory for the scalar roughness and the scalar transfer
coefficients over snow and sea ice, Bound.-Lay. Meteorol., 38, 159–184,
https://doi.org/10.1007/BF00121562, 1987.
Bai, X., Wang, J., Schwab, D. J., Yang, Y., Luo, L., Leshkevich, G. A., and
Liu, S.: Modeling 1993–2008 climatology of seasonal general circulation and
thermal structure in the Great Lakes using FVCOM, Ocean Model., 65, 40–63,
https://doi.org/10.1016/j.ocemod.2013.02.003, 2013.
Baldocchi, D., Hicks, B. B., and Meyers, T.: Measuring biosphere–atmosphere
exchanges of biologically related gases with micrometeorological methods,
Ecology, 69, 1331–1340, 1988.
Bélair, S., Brown, R., Mailhot, J., Bilodeau, B., and Crevier, L.-P.:
Operational Implementation of the ISBA Land Surface Scheme in the Canadian
Regional Weather Forecast Model. Part I: Warm Season Results, J. Hydrometeorol.,
4, 352–370, https://doi.org/10.1175/1525-7541(2003)4<352:OIOTIL>2.0.CO;2, 2003a.
Bélair, S., Brown, R., Mailhot, J., Bilodeau, B., and Crevier, L.-P.:
Operational Implementation of the ISBA Land Surface Scheme in the Canadian
Regional Weather Forecast Model. Part II: Cold Season Results, J. Hydrometeorol.,
4, 371–386, https://doi.org/10.1175/1525-7541(2003)4<371:OIOTIL>2.0.CO;2, 2003b.
Beletsky, D., Schwab, D. J., Roebber, P. J., McCormick, M. J., Miller, G. S.,
and Saylor, J. H.: Modeling wind-driven circulation during the March 1998
sediment resuspension event in Lake Michigan, J. Geophys. Res., 108, 3038,
https://doi.org/10.1029/2001JC001159, 2003.
Beletsky, D., Schwab, D., and McCormick, M.: Modeling the 1998-2003 summer
circulation and thermal structure in Lake Michigan, J. Geophys. Res.-Oceans,
111, 1–18, https://doi.org/10.1029/2005JC003222, 2006.
Beljaars, A. C. M.: The parametrization of surface fluxes in large-scale models
under free convection, Q. J. Roy. Meteorol. Soc., 121, 255–270, https://doi.org/10.1002/qj.49712152203, 1994.
Beljaars, A. C. M. and Holtslag, A. A. M.: Flux Parameterization over Land
Surfaces for Atmospheric Models, J. Appl. Meteorol., 30, 327–341,
https://doi.org/10.1175/1520-0450(1991)030<0327:FPOLSF>2.0.CO;2, 1991.
Benjamin, S. G., Weygandt, S. S., Brown, J. M., Hu, M., Alexander, C., Smirnova,
T. G., Olson, J. B., James, E., Dowell, D. C., Grell, G. A., Lin, H., Peckham,
S. E., Smith, T. L., Moninger, W. R., Kenyon, J., and Manikin, G. S.: A North
American hourly assimilation and model forecast cycle: The rapid refresh, Mon.
Weather Rev., 144, 1669–1694, https://doi.org/10.1175/MWR-D-15-0242.1, 2016.
Blanken, P. D., Black, T. a., Yang, P. C., Neumann, H. H., Nesic, Z., Staebler,
R., den Hartog, G., Novak, M. D., and Lee, X.: Energy balance and canopy
conductance of a boreal aspen forest: Partitioning overstory and understory
components, J. Geophys. Res., 102, 28915, https://doi.org/10.1029/97JD00193, 1997.
Blanken, P. D., Rouse, W. R., Culf, A. D., Spence, C., Boudreau, L. D., Jasper,
J. N., Kochtubajda, B., Schertzer, W. M., Marsh, P., and Verseghy, D.: Eddy
covariance measurements of evaporation from Great Slave Lake, Northwest
Territories, Canada, Water Resour. Res., 36, 1069–1077, https://doi.org/10.1029/1999WR900338, 2000.
Blanken, P. D., Rouse, W. R., and Schertzer, W.: The Time Scales of Evaporation
from Great Slave Lake, in: Atmospheric Dynamics of a Cold Region: The Mackenzie
GEWEX Study Experience, vol. II: Hydrol., edited by: Woo, M.-K., Springer,
New York, 181–196, 2008.
Blanken, P. D., Spence, C., Hedstrom, N., and Lenters, J. D.: Evaporation from
Lake Superior: 1. Physical controls and processes, J. Great Lakes Res., 37,
707–716, https://doi.org/10.1016/j.jglr.2011.08.009, 2011.
Bonan, G. B.: Sensitivity of a GCM simulation to inclusion of inland water
surfaces, J. Climate, 8, 2691–2704, https://doi.org/10.1175/1520-0442(1995)008<2691:SOAGST>2.0.CO;2, 1995.
Brutsaert, W.: A theory for local evaporation (or heat transfer) from rough and
smooth surfaces at ground level, Water Resour. Res., 11, 543–550,
https://doi.org/10.1029/WR011i004p00543, 1975.
Brutsaert, W.: Evaporation into the Atmosphere – Theory, History and
Applications, Springer, the Netherlands, 1982.
Businger, J. A., Wyngaard, J. C., Izumi, Y., and Bradley, E. F.: Flux-Profile
Relationships in the Atmospheric Surface Layer, J. Atmos. Sci., 28, 181–189,
https://doi.org/10.1175/1520-0469(1971)028<0181:FPRITA>2.0.CO;2, 1971.
Charnock, H.: Wind stress on a water surface, Q. J. Roy. Meteorol. Soc., 81,
639–640, https://doi.org/10.1002/qj.49708135027, 1955.
Chen, C., Beardsley, R. C., and Cowles, G.: An Unstructured Grid, Finite-Volume
Coastal Ocean Model FVCOM User Manual, Oceanography, 19, 78–89, https://doi.org/10.5670/oceanog.2006.92, 2006.
Chen, C., Beardsley, R., Cowles, G., Qi, J., Lai, Z., Gao, G., Stuebe, D., Xu,
Q., Xue, P., Ge, J., Hu, S., Chen, C., Beardsley, R., Cowles, G., Qi, J., Lai,
Z., Gao, G., Stuebe, D., Xu, Q., Xue, P., Ge, J., Hu, S., Ji, R., Tian, R.,
Huang, H., Wu, L., Huichan, L., Sun, Y., and Zhao, L.: An unstructured grid,
Finite-Volume Coastal Ocean Model FVCOM – User Manual, Tech. Rep., SMAST/UMASSD-13-0701,
Sch. Mar. Sci. Technol., Univ. Mass. Dartmouth, New Bedford., 416 pp., 2013.
Chen, F., Janjić, Z., and Mitchell, K.: Impact of Atmospheric Surface-layer
Parameterizations in the new Land-surface Scheme of the NCEP Mesoscale Eta Model,
Bound.-Lay. Meteorol., 85, 391–421, https://doi.org/10.1023/A:1000531001463, 1997.
Chu, P. Y., Kelley, J. G. W., Mott, G. V., Zhang, A., and Lang, G. A.:
Development, implementation, and skill assessment of the NOAA/NOS Great Lakes
Operational Forecast System, Ocean Dynam., 61, 1305–1316, https://doi.org/10.1007/s10236-011-0424-5, 2011.
Clites, A. H., Wang, J., Campbell, K. B., Gronewold, A. D., Assel, R., Bai, X.,
and Leshkevich, G. A.: Cold Water and High Ice Cover on Great Lakes in Spring 2014,
Earth Obs. Syst., 95, 305–312, 2014.
Croley, T. E.: Verifiable evaporation modeling on the Laurentian Great Lakes,
Water Resour. Res., 25, 781–792, https://doi.org/10.1029/WR025i005p00781, 1989a.
Croley, T. E.: Lumped Modeling of Laurentian Great Lakes Evaporation, Heat
Storage, and Energy Fluxes for Forecasting and Simulation, NOAA Tech. Memo.,
ERL GLERL, NOAA, Ann Arbor, Michigan, 1–48, 1989b.
Croley, T. E., Assel, R. A., and Arbor, A.: Great Lakes Evaporation Model
Sensitivities and Errors, Second Fed. Interag. Hydrol. Model. Conf. Subcomm.
Hydrol. Interag. Advis. Comm. Water Data, 9, 1–12, 2002.
Deacu, D., Fortin, V., Klyszejko, E., Spence, C., and Blanken, P. D.: Predicting
the net basin supply to the Great Lakes with a hydrometeorological model, J.
Hydrometeorol., 13, 1739–1759, https://doi.org/10.1175/JHM-D-11-0151.1, 2012.
Edson, J. B., Hinton, A. A., Prada, K. E., Hare, J. E., and Fairall, C. W.:
Direct covariance flux estimates from mobile platforms at sea, J. Atmos. Ocean.
Tech., 15, 547–562, https://doi.org/10.1175/1520-0426(1998)015<0547:DCFEFM>2.0.CO;2, 1998.
Edson, J. B., Jampana, V., Weller, R. a., Bigorre, S. P., Plueddemann, A. J.,
Fairall, C. W., Miller, S. D., Mahrt, L., Vickers, D., and Hersbach, H.: On the
Exchange of Momentum over the Open Ocean, J. Phys. Oceanogr., 43, 1589–1610,
https://doi.org/10.1175/JPO-D-12-0173.1, 2013.
Fairall, C. W., Bradley, E. F., Rogers, D. P., Edson, J. B., and Young, G. S.:
Bulk parameterization of air-sea fluxes for Tropical Ocean-Global Atmosphere
Coupled-Ocean Atmosohere Response Experiment, J. Geophys. Res., 101, 3747–3764, 1996a.
Fairall, C. W., Bradley, E. F., Godfrey, J. S., Wick, G. A., Edson, J. B., and
Young, G. S.: Cool-skin and warm-layer effects on sea surface temperature, J.
Geophys. Res., 101, 1295–1308, https://doi.org/10.1029/95JC03190, 1996b.
Fairall, C. W., Bradley, E. F., Hare, J. E., Grachev, A. A., and Edson, J. B.:
Bulk parameterization of air-sea fluxes: Updates and verification for the COARE
algorithm, J. Climate, 16, 571–591, https://doi.org/10.1175/1520-0442(2003)016<0571:BPOASF>2.0.CO;2, 2003.
Fujisaki-Manome, A., Fitzpatrick, L. E., Gronewold, A. D., Anderson, E. J.,
Lofgren, B. M., Spence, C., Chen, J., Shao, C., Wright, D. M., and Xiao, C.:
Turbulent Heat Fluxes during an Extreme Lake Effect Snow Event, J. Hydrometeorol.,
18, 3145–3163, https://doi.org/10.1175/JHM-D-17-0062.1, 2017.
FVCOM – Finite Volume Community Ocean Model source codes: http://fvcom.smast.umassd.edu/FVCOM/Source/code.htm,
last access: 1 December 2017.
Garratt, J. R.: The Atmospheric Boundary Layer, Cambridge University Press, Cambridge, 1992.
GLSEA – Great Lakes Surface Environmental Analysis: https://coastwatch.glerl.noaa.gov/glsea/doc/,
last access: 10 January 2018.
Great Lake Evaporation Network: About the Great Lakes Evaporation Network,
https://superiorwatersheds.org/GLEN/, last access: 10 January 2018.
Great Lakes Monthly Hydrologic Data: https://coastwatch.glerl.noaa.gov,
last access: 1 July 2018.
Gronewold, A. D. and Stow, C. A.: Water loss from the Great Lakes, Science,
343, 1084–1085, https://doi.org/10.1126/science.1249978, 2014.
Gronewold, A. D., Clites, A. H., Hunter, T. S., and Stow, C. A.: An appraisal
of the Great Lakes advanced hydrologic prediction system, J. Great Lakes Res.,
37, 577–583, https://doi.org/10.1016/j.jglr.2011.06.010, 2011.
Gronewold, A. D., Fortin, V., Lofgren, B., Clites, A., Stow, C. A., and Quinn,
F.: Coasts, water levels, and climate change: A Great Lakes perspective,
Climatic Change, 120, 697–711, https://doi.org/10.1007/s10584-013-0840-2, 2013.
Gu, H., Jin, J., Wu, Y., Ek, M. B., and Subin, Z. M.: Calibration and validation
of lake surface temperature simulations with the coupled WRF-lake model,
Climatic Change, 129, 471–483, https://doi.org/10.1007/s10584-013-0978-y, 2015.
Henderson-Sellers, B.: Calculating the surface energy balance for lake and
reservoir modeling: A review, Rev. Geophys., 24, 625–649, https://doi.org/10.1029/RG024i003p00625, 1986.
Holtslag, A. A. M., De Bruijn, E. I. F., and Pan, H.-L.: A High Resolution Air
Mass Transformation Model for Short-Range Weather Forecasting, Mon. Weather Rev.,
118, 1561–1575, https://doi.org/10.1175/1520-0493(1990)118<1561:AHRAMT>2.0.CO;2, 1990.
Horst, T. W.: A simple formula for attenuation of eddy fluxes measured with
first-order-response scalar sensors, Bound.-Lay. Meteorol., 82, 219–233,
https://doi.org/10.1023/A:1000229130034, 1997.
Hostetler, S. W. and Bartlein, P. J.: Simulation of Lake Evaporation with
Application to Modeling Lake Level Variations, Oregon, Water Resour. Res.,
26, 2603–2612, 1990.
Hostetler, S. W., Bates, G. T., and Giorgi, F.: Interactive coupling of a lake
thermal model with a regional climate model, J. Geophys. Res., 98, 5045,
https://doi.org/10.1029/92JD02843, 1993.
Hunke, E. C., Lipscomb, W. H., Turner, A. K., Jeffery, N., and Elliott, S.:
CICE: the Los Alamos Sea Ice Model documentation and software user's manual
LA-CC-06-012, Los Alamos, New Mexico, 1–116, 2015.
Hunter, T. S., Clites, A. H., Campbell, K. B., and Gronewold, A. D.: Development
and application of a North American Great Lakes hydrometeorological database – Part I:
Precipitation, evaporation, runoff, and air temperature, J. Great Lakes Res.,
41, 65–77, https://doi.org/10.1016/j.jglr.2014.12.006, 2015.
Jordan, R. E., Andreas, E. L., and Makshtas, A. P.: Heat budget of snow-covered
sea ice at North Pole 4, J. Geophys. Res., 104, 7785, https://doi.org/10.1029/1999JC900011, 1999.
Kantha, L. H. and Clayson, C. A.: Surface exchange processes, in: Small Scale
Processes in Geophysical Fluid Flows, Academic Press, San Diego, California, 417–509, 2000.
Kauffman, B. G. and Large, W. G.: The CCSM coupler, version 5.0.1, Technical
Note, Boulder, CO, USA, available at: http://www.cesm.ucar.edu/models/ccsm2.0.1/cpl5/users_guide.pdf
(last access: 27 May 2017), 2002.
Kraus, E. B. and Businger, J. A.: Atmosphere–Ocean Interaction, 2nd Edn.,
Oxford University Press, Oxford, 1995.
Lambin, J., Morrow, R., L.-L., F., Willis, J. K., Bonekamp, H., Lillibrige, J.,
Perbos, J., Zaouche, G., Vaze, P., Bannoura, W., Parisot, F., Thouvenot, E.,
Coutin-Faye, S., Lindstorm, E., and Mingogno, M.: The OSTM/Jason-2 Mission, Mar.
Geod., 33, 4–25, https://doi.org/10.1080/01490419.2010.491030, 2010.
Large, W. G. and Pond, S.: Open Ocean momentum flux measurements in moderate
to strong winds, J. Phys. Oceanogr., 11, 324–336, https://doi.org/10.1175/1520-0485(1981)011<0324:OOMFMI>2.0.CO;2, 1981.
Large, W. G., Mcwilliams, J. C., and Doney, S. C.: Oceanic Vertical Mixing – a
Review and a Model with a Nonlocal Boundary-Layer Parameterization, Rev. Geophys.,
32, 363–403, https://doi.org/10.1029/94rg01872, 1994.
Lenters, J. D.: Long-term Trends in the Seasonal Cycle of Great Lakes Water
Levels, J. Great Lakes Res., 27, 342–353, https://doi.org/10.1016/S0380-1330(01)70650-8, 2001.
Lenters, J. D., Anderton, John, B., Blanken, P. D., Spence, C., and Suyker, A.
E.: Great Lakes Evaporation: Implications for Water Levels Assessing the
Impacts of Climate Variability and Change on Great Lakes Evaporation:
Implications for water levels and the need for a coordinated observation
network, 2011 Proj. Reports, edited by: Brown, D., Bidwell, D., and Briley,
L., available from Gt. Lakes Integr. Sci. Assessments Cent., Ann Arbor, Michigan, 2013.
Liu, P. C. and Schwab, D. J.: A comparison of methods for estimating u*,
from given uz and air–sea temperature differences, J. Geophys. Res.,
92, 6488–6494, 1987.
Liu, W. T., Katosaros, K. B., and Businger, J. A.: Bulk Parameterization of
Air–Sea Exchanges of Heat and Water Vapor Including the Molecular Constraints
at the Interface, J. Atmos. Sci., 37, 2798–2800, https://doi.org/10.1175/1520-0469(1980)037<2798:COPOAS>2.0.CO;2, 1980.
Massman, W. J.: A simple method for estimating frequency response corrections
for eddy covariance systems, Agr. Forest Meteorol., 104, 185–198,
https://doi.org/10.1016/S0168-1923(00)00164-7, 2000.
Michalak, A. M., Anderson, E. J., Beletsky, D., Boland, S., Bosch, N. S.,
Bridgeman, T. B., Chaffin, J. D., Cho, K., Confesor, R., Daloglu, I., DePinto,
J. V., Evans, M. A., Fahnenstiel, G. L., He, L., Ho, J. C., Jenkins, L.,
Johengen, T. H., Kuo, K. C., LaPorte, E., Liu, X., McWilliams, M. R., Moore, M.
R., Posselt, D. J., Richards, R. P., Scavia, D., Steiner, A. L., Verhamme, E.,
Wright, D. M., and Zagorski, M. A.: Record-setting algal bloom in Lake Erie
caused by agricultural and meteorological trends consistent with expected future
conditions, P. Natl. Acad. Sci. USA, 110, 6448–6452, https://doi.org/10.1073/pnas.1216006110, 2013.
Mitchell, K., Ek, M., Wong, V., Lohmann, D., Koren, V., Schaake, J., Duan, Q.,
Gayno, G., Moore, B., Grunmann, P., Tarpley, D., Ramsay, B., Chen, F., Kim, J.,
Pan, H., Lin, Y., Marshall, C., Mahrt, L., Meyers, T., and Ruscher, P.: Noah
Land Surface Model (LSM) User's Guide, National Center for Atmospheric Research (NCAR),
Research Application Laboratory (RAL), available at: https://ral.ucar.edu/sites/default/files/public/product-tool/unified-noah-lsm/Noah_LSM_USERGUIDE_2.7.1.pdf
(last access: October 2018), 2005.
Moukomla, S. and Blanken, P. D.: Remote sensing of the North American Laurentian
Great Lakes' surface temperature, Remote Sensing, 8, 1–15, https://doi.org/10.3390/rs8040286, 2016.
Moukomla, S. and Blanken, P. D.: The Estimation of the North American Great
Lakes Turbulent Fluxes Using Satellite Remote Sensing and MERRA Reanalysis
Data, Remote Sensing, 9, 141, https://doi.org/10.3390/rs9020141, 2017.
Obukhov, A. M.: Turbulence in an atmosphere with a non-uniform temperature,
Bound.-Lay. Meteorol., 2, 7–29, https://doi.org/10.1007/BF00718085, 1971.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Drewniak, B., Huang, M., Koven,
C. D., Levis, S., Li, F., Riley, W. J., Subin, Z. M., Swenson, S. C., Thornton,
P. E., Bozbiyik, A., Fisher, R., Heald, C. L., Kluzek, E., Lamarque, J.-F.,
Lawrence, P. J., Leung, L. R., Lipscomb, W., Muszala, S., Ricciuto, D. M.,
Sacks, W., Sun, Y., Tang, J., and Yang, Z.-L.: Technical description of
version 4.5 of the Community Land Model (CLM), NCAR Technical Note:
NCAR/TN-503+STR, National Center for Atmospheric Research (NCAR), Boulder, CO,
USA, https://doi.org/10.5065/D6RR1W7M, 2013.
Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., and
Schlax, M. G.: Daily high-resolution-blended analyses for sea surface
temperature, J. Climate, 20, 5473–5496, https://doi.org/10.1175/2007JCLI1824.1, 2007.
Rowe, M. D., Anderson, E. J., Wang, J., and Vanderploeg, H. A.: Modeling the
effect of invasive quagga mussels on the spring phytoplankton bloom in Lake
Michigan, J. Great Lakes Res., 41, 49–65, https://doi.org/10.1016/j.jglr.2014.12.018, 2015.
Skamarock, W. C., Klemp, J. B., Dudhi, J., Gill, D. O., Barker, D. M., Duda, M.
G., Huang, X.-Y., Wang, W., and Powers, J. G.: A Description of the Advanced
Research WRF Version 3, NCAR Technical Note: NCAR/TN-475+STR, National Center
for Atmospheric Research (NCAR), 1–113, https://doi.org/10.5065/D6DZ069T, 2008.
Smith, S. D.: Coefficients for Sea Surface Wind Stress, Heat Flux, and Wind
Profiles as a Function of Wind Speed and Temperature, J. Geophys. Res.,
93, 15467–15472, 1988.
Spence, C., Blanken, P. D., Hedstrom, N., Fortin, V., and Wilson, H.: Evaporation
from Lake Superior: 2. Spatial distribution and variability, J. Great Lakes Res.,
37, 717–724, https://doi.org/10.1016/j.jglr.2011.08.013, 2011.
Spence, C., Blanken, P. D., Lenters, J. D., and Hedstrom, N.: The importance
of spring and autumn atmospheric conditions for the evaporation regime of Lake
Superior, J. Hydrometeorol., 14, 1647–1658, https://doi.org/10.1175/JHM-D-12-0170.1, 2013.
Subin, Z. M., Riley, W. J., and Mironov, D.: An improved lake model for climate
simulations: Model structure, evaluation, and sensitivity analyses in CESM1, J.
Adv. Model. Earth Syst., 4, 1–27, https://doi.org/10.1029/2011MS000072, 2012.
Van Cleave, K., Lenters, J. D., Wang, J., and Verhamme, E. M.: A regime shift
in Lake Superior ice cover, evaporation, and water temperature following the
warm El Niño winter of 1997–98, Limnol. Oceanogr., 59, 1889–1898,
https://doi.org/10.4319/lo.2014.59.6.1889, 2014.
Wang, J., Hu, H., Schwab, D., Leshkevich, G., Beletsky, D., Hawley, N., and
Clites, A.: Development of the Great Lakes Ice-circulation Model (GLIM):
Application to Lake Erie in 2003–2004, J. Great Lakes Res., 36, 425–436,
https://doi.org/10.1016/j.jglr.2010.04.002, 2010.
Webb, E. K., Pearman, G. I., and Leuning, R.: Correction of flux measurements
for density effects due to heat and water vapour transfer, Q. J. Roy. Meteorol.
Soc., 106, 85–100, https://doi.org/10.1002/qj.49710644707, 1980.
WRF-ARW – Weather Research and Forecasting Model source codes: http://www2.mmm.ucar.edu/wrf/users/
(last access: 1 December 2017), https://doi.org/10.5065/D6MK6B4K, 2017.
Wright, D. M., Posselt, D. J., and Steiner, A. L.: Sensitivity of lake-effect
snowfall to lake ice vover and temperature in the Great Lakes region, Mon.
Weather Rev., 141, 670–689, https://doi.org/10.1175/MWR-D-12-00038.1, 2013.
Xiao, C., Lofgren, B. M., Wang, J., and Chu, P. Y.: Improving the lake scheme
within a coupled WRF-lake model in the Laurentian Great Lakes, J. Adv. Model.
Earth Syst., 8, 1969–1985, https://doi.org/10.1002/2016MS000717, 2016.
Xue, P., Schwab, D. J., and Hu, S.: An investigation of the thermal response
tometeorological forcing in a hydrodynamic model of Lake Superior, J. Geophys.
Res.-Oceans, 120, 5233–5253, https://doi.org/10.1002/jgrc.20224, 2015.
Xue, P., Pal, J. S., Ye, X., Lenters, J. D., Huang, C., and Chu, P. Y.:
Improving the simulation of large lakes in regional climate modeling: Two-way
lake-atmosphere coupling with a 3D hydrodynamic model of the great lakes, J.
Climate, 30, 1605–1627, https://doi.org/10.1175/JCLI-D-16-0225.1, 2017.
Zeng, X., Zhao, M., and Dickinson, R. E.: Intercomparison of bulk aerodynamic
algorithms for the computation of sea surface fluxes using TOGA COARE and TAO
data, J. Climate, 11, 2628–2644, https://doi.org/10.1175/1520-0442(1998)011<2628:IOBAAF>2.0.CO;2, 1998.
Short summary
The authors evaluated several algorithms of heat loss and evaporation simulation by comparing with direct measurements at four offshore flux towers in the North American Great Lakes. The algorithms reproduced the seasonal cycle of heat loss and evaporation reasonably, but some algorithms significantly overestimated them during fall to early winter. This was due to false assumption of roughness length scales for temperature and humidity and was improved by employing a correct parameterization.
The authors evaluated several algorithms of heat loss and evaporation simulation by comparing...
