Articles | Volume 20, issue 6
https://doi.org/10.5194/hess-20-2403-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-2403-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
21 Jun 2016
Research article |
| 21 Jun 2016
Modelling evapotranspiration during precipitation deficits: identifying critical processes in a land surface model
Anna M. Ukkola
CORRESPONDING AUTHOR
ARC Centre of Excellence for Climate System Science, University of
New South Wales, Kensington, NSW 2052, Australia
Andy J. Pitman
ARC Centre of Excellence for Climate System Science, University of
New South Wales, Kensington, NSW 2052, Australia
Climate Change
Research Centre, University of New South Wales, Kensington, NSW 2052,
Australia
Mark Decker
ARC Centre of Excellence for Climate System Science, University of
New South Wales, Kensington, NSW 2052, Australia
Climate Change
Research Centre, University of New South Wales, Kensington, NSW 2052,
Australia
Martin G. De Kauwe
Department of Biological Sciences, Macquarie University,
Balaclava Road, North Ryde, NSW 2109, Australia
Gab Abramowitz
ARC Centre of Excellence for Climate System Science, University of
New South Wales, Kensington, NSW 2052, Australia
Climate Change
Research Centre, University of New South Wales, Kensington, NSW 2052,
Australia
Jatin Kala
ARC Centre of Excellence for Climate System Science, University of
New South Wales, Kensington, NSW 2052, Australia
Murdoch
University, School of Veterinary and Life Sciences, Environmental and
Conservation Sciences, Murdoch, WA 6150, Australia
Ying-Ping Wang
CSIRO Ocean and Atmosphere, Aspendale, VIC 3195, Australia
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Anthony P. Walker, Ming Ye, Dan Lu, Martin G. De Kauwe, Lianhong Gu, Belinda E. Medlyn, Alistair Rogers, and Shawn P. Serbin
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Ned Haughton, Gab Abramowitz, Martin G. De Kauwe, and Andy J. Pitman
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Revised manuscript has not been submitted
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This study presents a global estimate of land carbon uptake through photosynthesis. We make use satellite chlorophyll fluorescence measurements, a visible indicator of photosynthesis, to optimize model parameters and then use the optimized model to estimate photosynthetic carbon uptake. This provides a new tool that can combine measurements and observations in a systematic way and maximise the use of chlorophyll fluorescence to improve our understanding of the land carbon cycle.
Donghai Wu, Philippe Ciais, Nicolas Viovy, Alan K. Knapp, Kevin Wilcox, Michael Bahn, Melinda D. Smith, Sara Vicca, Simone Fatichi, Jakob Zscheischler, Yue He, Xiangyi Li, Akihiko Ito, Almut Arneth, Anna Harper, Anna Ukkola, Athanasios Paschalis, Benjamin Poulter, Changhui Peng, Daniel Ricciuto, David Reinthaler, Guangsheng Chen, Hanqin Tian, Hélène Genet, Jiafu Mao, Johannes Ingrisch, Julia E. S. M. Nabel, Julia Pongratz, Lena R. Boysen, Markus Kautz, Michael Schmitt, Patrick Meir, Qiuan Zhu, Roland Hasibeder, Sebastian Sippel, Shree R. S. Dangal, Stephen Sitch, Xiaoying Shi, Yingping Wang, Yiqi Luo, Yongwen Liu, and Shilong Piao
Biogeosciences, 15, 3421–3437, https://doi.org/10.5194/bg-15-3421-2018, https://doi.org/10.5194/bg-15-3421-2018, 2018
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Our results indicate that most ecosystem models do not capture the observed asymmetric responses under normal precipitation conditions, suggesting an overestimate of the drought effects and/or underestimate of the watering impacts on primary productivity, which may be the result of inadequate representation of key eco-hydrological processes. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.
Natthachet Tangdamrongsub, Shin-Chan Han, Mark Decker, In-Young Yeo, and Hyungjun Kim
Hydrol. Earth Syst. Sci., 22, 1811–1829, https://doi.org/10.5194/hess-22-1811-2018, https://doi.org/10.5194/hess-22-1811-2018, 2018
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We present a new approach to improve the water storage estimate. Our approach combines GRACE's raw data (least-squares normal equation) with the results from the Community Atmosphere Land Exchange (CABLE) model. No post-processing filter is applied to GRACE data, and the full GRACE signal and error information are exploited. The approach is applied over 10 Australian river basins, and the evident improvement of the water storage estimate, particularly groundwater component, is clearly observed.
Sanaa Hobeichi, Gab Abramowitz, Jason Evans, and Anna Ukkola
Hydrol. Earth Syst. Sci., 22, 1317–1336, https://doi.org/10.5194/hess-22-1317-2018, https://doi.org/10.5194/hess-22-1317-2018, 2018
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We present a new global ET dataset and associated uncertainty with monthly temporal resolution for 2000–2009 and 0.5 grid cell size. Six existing gridded ET products are combined using a weighting approach trained by observational datasets from 159 FLUXNET sites. We confirm that point-based estimates of flux towers provide information at the grid scale of these products. We also show that the weighted product performs better than 10 different existing global ET datasets in a range of metrics.
Nadja Herger, Gab Abramowitz, Reto Knutti, Oliver Angélil, Karsten Lehmann, and Benjamin M. Sanderson
Earth Syst. Dynam., 9, 135–151, https://doi.org/10.5194/esd-9-135-2018, https://doi.org/10.5194/esd-9-135-2018, 2018
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Users presented with large multi-model ensembles commonly use the equally weighted model mean as a best estimate, ignoring the issue of near replication of some climate models. We present an efficient and flexible tool that finds a subset of models with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments.
Ned Haughton, Gab Abramowitz, and Andy J. Pitman
Geosci. Model Dev., 11, 195–212, https://doi.org/10.5194/gmd-11-195-2018, https://doi.org/10.5194/gmd-11-195-2018, 2018
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Previous studies indicate that fluxes of heat, water, and carbon between the land surface and atmosphere are substantially more predictable than the performance of the current crop of land surface models would indicate. This study uses simple empirical models to estimate the amount of useful information in meteorological forcings that is available for predicting land surface fluxes. These models can be used as benchmarks for land surface models and may help identify areas ripe for improvement.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gabriel Abramowitz, Martin G. De Kauwe, Bradley Evans, Vanessa Haverd, Longhui Li, Caitlin Moore, Youngryel Ryu, Simon Scheiter, Stanislaus J. Schymanski, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 14, 4711–4732, https://doi.org/10.5194/bg-14-4711-2017, https://doi.org/10.5194/bg-14-4711-2017, 2017
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This paper attempts to review some of the current challenges faced by the modelling community in simulating the behaviour of savanna ecosystems. We provide a particular focus on three dynamic processes (phenology, root-water access, and fire) that are characteristic of savannas, which we believe are not adequately represented in current-generation terrestrial biosphere models. We highlight reasons for these misrepresentations, possible solutions and a future direction for research in this area.
Martin G. De Kauwe, Belinda E. Medlyn, Jürgen Knauer, and Christopher A. Williams
Biogeosciences, 14, 4435–4453, https://doi.org/10.5194/bg-14-4435-2017, https://doi.org/10.5194/bg-14-4435-2017, 2017
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Understanding the sensitivity of transpiration to stomatal conductance is critical to simulating the water cycle. This sensitivity is a function of the degree of coupling between the vegetation and the atmosphere. We combined an extensive literature summary with estimates of coupling derived from FLUXNET data. We found notable departures from the values previously reported. These data form a model benchmarking metric to test existing coupling assumptions.
Richard Wartenburger, Martin Hirschi, Markus G. Donat, Peter Greve, Andy J. Pitman, and Sonia I. Seneviratne
Geosci. Model Dev., 10, 3609–3634, https://doi.org/10.5194/gmd-10-3609-2017, https://doi.org/10.5194/gmd-10-3609-2017, 2017
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This article analyses regional changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. Readers are encouraged to use the online tool for visualization of specific indices of interest, e.g. to assess their response to 1.5 or 2 °C global warming.
Anna M. Ukkola, Ned Haughton, Martin G. De Kauwe, Gab Abramowitz, and Andy J. Pitman
Geosci. Model Dev., 10, 3379–3390, https://doi.org/10.5194/gmd-10-3379-2017, https://doi.org/10.5194/gmd-10-3379-2017, 2017
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Flux towers measure energy, carbon dioxide and water vapour fluxes. These data have become essential for evaluating land surface models (LSMs) – key tools for projecting future climate change. However, these data as released are not immediately usable with LSMs and must be post-processed to change units, screened for missing data and gap-filling. We present an open-source R package that transforms flux tower measurements into a format directly usable by LSMs.
Rachel M. Law, Tilo Ziehn, Richard J. Matear, Andrew Lenton, Matthew A. Chamberlain, Lauren E. Stevens, Ying-Ping Wang, Jhan Srbinovsky, Daohua Bi, Hailin Yan, and Peter F. Vohralik
Geosci. Model Dev., 10, 2567–2590, https://doi.org/10.5194/gmd-10-2567-2017, https://doi.org/10.5194/gmd-10-2567-2017, 2017
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The paper describes a version of the Australian Community Climate and Earth System Simulator that has been enabled to simulate the carbon cycle, which is designated ACCESS-ESM1. The model performance for pre-industrial conditions is assessed and land and ocean carbon fluxes are found to be simulated realistically.
Yiqi Luo, Zheng Shi, Xingjie Lu, Jianyang Xia, Junyi Liang, Jiang Jiang, Ying Wang, Matthew J. Smith, Lifen Jiang, Anders Ahlström, Benito Chen, Oleksandra Hararuk, Alan Hastings, Forrest Hoffman, Belinda Medlyn, Shuli Niu, Martin Rasmussen, Katherine Todd-Brown, and Ying-Ping Wang
Biogeosciences, 14, 145–161, https://doi.org/10.5194/bg-14-145-2017, https://doi.org/10.5194/bg-14-145-2017, 2017
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Climate change is strongly regulated by land carbon cycle. However, we lack the ability to predict future land carbon sequestration. Here, we develop a novel framework for understanding what determines the direction and rate of future change in land carbon storage. The framework offers a suite of new approaches to revolutionize land carbon model evaluation and improvement.
Eva A. Kowalczyk, Lauren E. Stevens, Rachel M. Law, Ian N. Harman, Martin Dix, Charmaine N. Franklin, and Ying-Ping Wang
Geosci. Model Dev., 9, 2771–2791, https://doi.org/10.5194/gmd-9-2771-2016, https://doi.org/10.5194/gmd-9-2771-2016, 2016
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This paper compares two ACCESS model versions that differ only in their land surface scheme. Differences in the simulated present-day climate are attributed to differences in the representation of various land surface processes.
Rashid Rafique, Jianyang Xia, Oleksandra Hararuk, Ghassem R. Asrar, Guoyong Leng, Yingping Wang, and Yiqi Luo
Earth Syst. Dynam., 7, 649–658, https://doi.org/10.5194/esd-7-649-2016, https://doi.org/10.5194/esd-7-649-2016, 2016
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Traceability analysis was used to diagnose the causes of differences in simulating ecosystem carbon storage capacity between two land models: CLMA-CASA and CABLE. Results showed that the simulated ecosystem carbon storage capacity is largely influenced by the photosynthesis parameterization, residence time and organic matter decomposition.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gab Abramowitz, Martin G. De Kauwe, Remko Duursma, Bradley Evans, Vanessa Haverd, Longhui Li, Youngryel Ryu, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 13, 3245–3265, https://doi.org/10.5194/bg-13-3245-2016, https://doi.org/10.5194/bg-13-3245-2016, 2016
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In this study we assess how well terrestrial biosphere models perform at predicting water and carbon cycling for savanna ecosystems. We apply our models to five savanna sites in Northern Australia and highlight key causes for model failure. Our assessment of model performance uses a novel benchmarking system that scores a model’s predictive ability based on how well it is utilizing its driving information. On average, we found the models as a group display only moderate levels of performance.
Y. P. Wang, J. Jiang, B. Chen-Charpentier, F. B. Agusto, A. Hastings, F. Hoffman, M. Rasmussen, M. J. Smith, K. Todd-Brown, Y. Wang, X. Xu, and Y. Q. Luo
Biogeosciences, 13, 887–902, https://doi.org/10.5194/bg-13-887-2016, https://doi.org/10.5194/bg-13-887-2016, 2016
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Comparing two nonlinear microbial models, we found that,
in response to warming, soil C decreases in one model but can increase or decrease in the other model, and sensitivity of priming response to carbon input increases with soil T in one model but decreases in the other model
Significance: these differences in the responses can be used to discern which model is more realistic, which will improve our understanding of the significance of soil microbial processes in the terrestrial C cycle.
M. G. De Kauwe, S.-X. Zhou, B. E. Medlyn, A. J. Pitman, Y.-P. Wang, R. A. Duursma, and I. C. Prentice
Biogeosciences, 12, 7503–7518, https://doi.org/10.5194/bg-12-7503-2015, https://doi.org/10.5194/bg-12-7503-2015, 2015
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Future climate change has the potential to increase drought in many regions of the globe. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art models currently assume the same drought sensitivity for all vegetation. Our results indicate that models will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.
J. Kala, M. G. De Kauwe, A. J. Pitman, R. Lorenz, B. E. Medlyn, Y.-P Wang, Y.-S Lin, and G. Abramowitz
Geosci. Model Dev., 8, 3877–3889, https://doi.org/10.5194/gmd-8-3877-2015, https://doi.org/10.5194/gmd-8-3877-2015, 2015
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We implement a new stomatal conductance scheme within a land surface model coupled to a global climate model. The new model differs from the default in that it allows model parameters to vary by the different plant functional types, derived from global synthesis of observations. We show that the new scheme results in improvements in the model climatology and improves existing biases in warm temperature extremes by up to 10-20% over the boreal forests during summer.
M. Decker, A. Pitman, and J. Evans
Hydrol. Earth Syst. Sci., 19, 3433–3447, https://doi.org/10.5194/hess-19-3433-2015, https://doi.org/10.5194/hess-19-3433-2015, 2015
I. C. Prentice, X. Liang, B. E. Medlyn, and Y.-P. Wang
Atmos. Chem. Phys., 15, 5987–6005, https://doi.org/10.5194/acp-15-5987-2015, https://doi.org/10.5194/acp-15-5987-2015, 2015
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Land surface models (LSMs) describe how carbon and water fluxes react to environmental change. They are key component of climate models, yet they differ enormously. Many perform poorly, despite having many parameters. We outline a development strategy emphasizing robustness, reliability and realism, none of which is guaranteed by complexity alone. We propose multiple constraints, benchmarking and data assimilation, and representing unresolved processes stochastically, as tools in this endeavour.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
M. G. De Kauwe, J. Kala, Y.-S. Lin, A. J. Pitman, B. E. Medlyn, R. A. Duursma, G. Abramowitz, Y.-P. Wang, and D. G. Miralles
Geosci. Model Dev., 8, 431–452, https://doi.org/10.5194/gmd-8-431-2015, https://doi.org/10.5194/gmd-8-431-2015, 2015
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Stomatal conductance affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the CABLE land surface model (LSM). The new implementation resulted in a large reduction in the annual fluxes of transpiration across evergreen needleleaf, tundra and C4 grass regions. We conclude that optimisation theory can yield a tractable approach to predicting stomatal conductance in LSMs.
J.-F. Exbrayat, A. J. Pitman, and G. Abramowitz
Biogeosciences, 11, 6999–7008, https://doi.org/10.5194/bg-11-6999-2014, https://doi.org/10.5194/bg-11-6999-2014, 2014
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We use a reduced complexity soil organic carbon (SOC) model to address the influence of two parameters on the response of SOC stocks to climate change: baseline turnover time (k) and temperature sensitivity of decomposition (Q10). In our model, k determines SOC stocks and the magnitude of the response to climate change (from 1850 to 2100 under RCP 8.5) while Q10 drives its sign. We dismiss unlikely simulations using global SOC data to reduce the uncertainty in projections and parameter values.
J.-F. Exbrayat, A. J. Pitman, and G. Abramowitz
Geosci. Model Dev., 7, 2683–2692, https://doi.org/10.5194/gmd-7-2683-2014, https://doi.org/10.5194/gmd-7-2683-2014, 2014
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Pre-industrial soil organic carbon (SOC) stocks vary 6-fold in models used in the 5th IPCC Assessment Report. This paper shows that this range is largely determined by model-specific responses of microbal decomposition during the equilibration procedure. As SOC stocks are maintained through the present and to 2100 almost unchanged, we propose that current SOC observations could be used to constrain this equilibration procedure and thereby reduce the uncertainty in climate change projections.
J. Kala, J. P. Evans, A. J. Pitman, C. B. Schaaf, M. Decker, C. Carouge, D. Mocko, and Q. Sun
Geosci. Model Dev., 7, 2121–2140, https://doi.org/10.5194/gmd-7-2121-2014, https://doi.org/10.5194/gmd-7-2121-2014, 2014
Y. P. Wang, B. C. Chen, W. R. Wieder, M. Leite, B. E. Medlyn, M. Rasmussen, M. J. Smith, F. B. Agusto, F. Hoffman, and Y. Q. Luo
Biogeosciences, 11, 1817–1831, https://doi.org/10.5194/bg-11-1817-2014, https://doi.org/10.5194/bg-11-1817-2014, 2014
R. Lorenz, A. J. Pitman, M. G. Donat, A. L. Hirsch, J. Kala, E. A. Kowalczyk, R. M. Law, and J. Srbinovsky
Geosci. Model Dev., 7, 545–567, https://doi.org/10.5194/gmd-7-545-2014, https://doi.org/10.5194/gmd-7-545-2014, 2014
J.-F. Exbrayat, A. J. Pitman, Q. Zhang, G. Abramowitz, and Y.-P. Wang
Biogeosciences, 10, 7095–7108, https://doi.org/10.5194/bg-10-7095-2013, https://doi.org/10.5194/bg-10-7095-2013, 2013
Q. Zhang, A. J. Pitman, Y. P. Wang, Y. J. Dai, and P. J. Lawrence
Earth Syst. Dynam., 4, 333–345, https://doi.org/10.5194/esd-4-333-2013, https://doi.org/10.5194/esd-4-333-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
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
Global total precipitable water variations and trends during 1958–2021
Spatial variability of seasonal precipitation lapse rates in complex topographical regions – application in France
Understanding the influence of “hot” models in climate impact studies: a hydrological perspective
A semi-parametric hourly space–time weather generator
A principal-component-based strategy for regionalisation of precipitation intensity–duration–frequency (IDF) statistics
Accounting for precipitation asymmetry in a multiplicative random cascade disaggregation model
Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach
A genetic particle filter scheme for univariate snow cover assimilation into Noah-MP model across snow climates
Investigating the response of land–atmosphere interactions and feedbacks to spatial representation of irrigation in a coupled modeling framework
Validation of precipitation reanalysis products for rainfall-runoff modelling in Slovenia
Identification of compound drought and heatwave events on a daily scale and across four seasons
Statistical post-processing of precipitation forecasts using circulation classifications and spatiotemporal deep neural networks
Sensitivity of the pseudo-global warming method under flood conditions: a case study from the northeastern US
Hybrid forecasting: blending climate predictions with AI models
Sensitivities of subgrid-scale physics schemes, meteorological forcing, and topographic radiation in atmosphere-through-bedrock integrated process models: a case study in the Upper Colorado River basin
Simulating one century (1902–2009) of river discharges, low flow sequences and flood events of an alpine river from large-scale atmospheric information
Local moisture recycling across the globe
How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation?
Regionalisation of rainfall depth–duration–frequency curves with different data types in Germany
The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting
Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models
Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System
Spatial distribution of oceanic moisture contributions to precipitation over the Tibetan Plateau
Ensemble streamflow prediction considering the influence of reservoirs in Narmada River Basin, India
Declining water resources in response to global warming and changes in atmospheric circulation patterns over southern Mediterranean France
Linking the complementary evaporation relationship with the Budyko framework for ungauged areas in Australia
Risks of seasonal extreme rainfall events in Bangladesh under 1.5 and 2.0 °C warmer worlds – how anthropogenic aerosols change the story
Pan evaporation is increased by submerged macrophytes
Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning: a meta-analysis
Characterizing basin-scale precipitation gradients in the Third Pole region using a high-resolution atmospheric simulation-based dataset
Assessing decadal to centennial scale nonstationary variability in meteorological drought trends
A comparison of hydrological models with different level of complexity in Alpine regions in the context of climate change
Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing
Hydrological concept formation inside long short-term memory (LSTM) networks
A two-step merging strategy for incorporating multi-source precipitation products and gauge observations using machine learning classification and regression over China
Hydrometeorological evaluation of two nowcasting systems for Mediterranean heavy precipitation events with operational considerations
On the links between sub-seasonal clustering of extreme precipitation and high discharge in Switzerland and Europe
Regional, multi-decadal analysis on the Loire River basin reveals that stream temperature increases faster than air temperature
Investigating the response of leaf area index to droughts in southern African vegetation using observations and model simulations
Recent decrease in summer precipitation over the Iberian Peninsula closely links to reduction in local moisture recycling
Exploring the possible role of satellite-based rainfall data in estimating inter- and intra-annual global rainfall erosivity
Critical transitions in the hydrological system: early-warning signals and network analysis
Testing a maximum evaporation theory over saturated land: implications for potential evaporation estimation
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
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Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
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A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
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We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
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Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
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Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-301, https://doi.org/10.5194/hess-2023-301, 2024
Revised manuscript accepted for HESS
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Global warming occurs at a rate of 0.15 K dec-1, resulting in about 5 % K-1 of water vapor response to temperature from 1958 to 2021. Terrestrial areas experienced larger warming than the ocean, with a ratio of 2:1. The total precipitable water change in response to surface temperature changes showed larger variations of 5–11 % K-1 over oceans than over land. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
EGUsphere, https://doi.org/10.5194/egusphere-2023-3124, https://doi.org/10.5194/egusphere-2023-3124, 2024
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Precipitation Lapse Rates (PLRs), defined as the increasing or decreasing rate of precipitation amounts with elevation, influence high-altitude precipitation estimation. This study presents an assessment of PLRs on 2,748 small catchments in France over four seasons. These evaluations emphasize the benefit of convection-permitting regional climate model simulations to study the spatial variability of seasonal PLRs at a fine scale.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
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Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
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Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
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Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
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In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, and Peipei Xu
Hydrol. Earth Syst. Sci., 27, 2919–2933, https://doi.org/10.5194/hess-27-2919-2023, https://doi.org/10.5194/hess-27-2919-2023, 2023
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This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
Patricia Lawston-Parker, Joseph A. Santanello Jr., and Nathaniel W. Chaney
Hydrol. Earth Syst. Sci., 27, 2787–2805, https://doi.org/10.5194/hess-27-2787-2023, https://doi.org/10.5194/hess-27-2787-2023, 2023
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Irrigation has been shown to impact weather and climate, but it has only recently been considered in prediction models. Prescribing where (globally) irrigation takes place is important to accurately simulate its impacts on temperature, humidity, and precipitation. Here, we evaluated three different irrigation maps in a weather model and found that the extent and intensity of irrigated areas and their boundaries are important drivers of weather impacts resulting from human practices.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
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For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
EGUsphere, https://doi.org/10.5194/egusphere-2023-147, https://doi.org/10.5194/egusphere-2023-147, 2023
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This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves across four seasons. From that, we could know the drought (or heatwave) starts on which day and ends on which day. We found an increase in the frequency of heatwaves and the co-occurring droughts and heatwaves in Belgium caused by climate change. We also found that different months have different chances of co-occurring droughts and heatwaves.
Tuantuan Zhang, Zhongmin Liang, Wentao Li, Jun Wang, Yiming Hu, and Binquan Li
Hydrol. Earth Syst. Sci., 27, 1945–1960, https://doi.org/10.5194/hess-27-1945-2023, https://doi.org/10.5194/hess-27-1945-2023, 2023
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We use circulation classifications and spatiotemporal deep neural networks to correct raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information. We find that the method not only captures the westward and northward movement of the western Pacific subtropical high but also shows substantially higher bias-correction capabilities than existing standard methods in terms of spatial scale, timescale, and intensity.
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
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We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
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Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Zexuan Xu, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman
Hydrol. Earth Syst. Sci., 27, 1771–1789, https://doi.org/10.5194/hess-27-1771-2023, https://doi.org/10.5194/hess-27-1771-2023, 2023
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The goal of this study is to understand the uncertainties of different modeling configurations for simulating hydroclimate responses in the mountainous watershed. We run a group of climate models with various configurations and evaluate them against various reference datasets. This paper integrates a climate model and a hydrology model to have a full understanding of the atmospheric-through-bedrock hydrological processes.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-92, https://doi.org/10.5194/hess-2023-92, 2023
Revised manuscript accepted for HESS
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the Upper Rhône alpine River, provided that the weather scenarios are bias-corrected.
Jolanda J. E. Theeuwen, Arie Staal, Obbe A. Tuinenburg, Bert V. M. Hamelers, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 27, 1457–1476, https://doi.org/10.5194/hess-27-1457-2023, https://doi.org/10.5194/hess-27-1457-2023, 2023
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Evaporation changes over land affect rainfall over land via moisture recycling. We calculated the local moisture recycling ratio globally, which describes the fraction of evaporated moisture that rains out within approx. 50 km of its source location. This recycling peaks in summer as well as over wet and elevated regions. Local moisture recycling provides insight into the local impacts of evaporation changes and can be used to study the influence of regreening on local rainfall.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
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Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Bora Shehu, Winfried Willems, Henrike Stockel, Luisa-Bianca Thiele, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 1109–1132, https://doi.org/10.5194/hess-27-1109-2023, https://doi.org/10.5194/hess-27-1109-2023, 2023
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Rainfall volumes at varying duration and frequencies are required for many engineering water works. These design volumes have been provided by KOSTRA-DWD in Germany. However, a revision of the KOSTRA-DWD is required, in order to consider the recent state-of-the-art and additional data. For this purpose, in our study, we investigate different methods and data available to achieve the best procedure that will serve as a basis for the development of the new KOSTRA-DWD product.
Sandra M. Hauswirth, Marc F. P. Bierkens, Vincent Beijk, and Niko Wanders
Hydrol. Earth Syst. Sci., 27, 501–517, https://doi.org/10.5194/hess-27-501-2023, https://doi.org/10.5194/hess-27-501-2023, 2023
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Forecasts on water availability are important for water managers. We test a hybrid framework based on machine learning models and global input data for generating seasonal forecasts. Our evaluation shows that our discharge and surface water level predictions are able to create reliable forecasts up to 2 months ahead. We show that a hybrid framework, developed for local purposes and combined and rerun with global data, can create valuable information similar to large-scale forecasting models.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
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Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Shaun Harrigan, Ervin Zsoter, Hannah Cloke, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023, https://doi.org/10.5194/hess-27-1-2023, 2023
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Real-time river discharge forecasts and reforecasts from the Global Flood Awareness System (GloFAS) have been made publicly available, together with an evaluation of forecast skill at the global scale. Results show that GloFAS is skillful in over 93 % of catchments in the short (1–3 d) and medium range (5–15 d) and skillful in over 80 % of catchments in the extended lead time (16–30 d). Skill is summarised in a new layer on the GloFAS Web Map Viewer to aid decision-making.
Ying Li, Chenghao Wang, Ru Huang, Denghua Yan, Hui Peng, and Shangbin Xiao
Hydrol. Earth Syst. Sci., 26, 6413–6426, https://doi.org/10.5194/hess-26-6413-2022, https://doi.org/10.5194/hess-26-6413-2022, 2022
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Spatial quantification of oceanic moisture contribution to the precipitation over the Tibetan Plateau (TP) contributes to the reliable assessments of regional water resources and the interpretation of paleo archives in the region. Based on atmospheric reanalysis datasets and numerical moisture tracking, this work reveals the previously underestimated oceanic moisture contributions brought by the westerlies in winter and the overestimated moisture contributions from the Indian Ocean in summer.
Urmin Vegad and Vimal Mishra
Hydrol. Earth Syst. Sci., 26, 6361–6378, https://doi.org/10.5194/hess-26-6361-2022, https://doi.org/10.5194/hess-26-6361-2022, 2022
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Floods cause enormous damage to infrastructure and agriculture in India. However, the utility of ensemble meteorological forecast for hydrologic prediction has not been examined. Moreover, Indian river basins have a considerable influence of reservoirs that alter the natural flow variability. We developed a hydrologic modelling-based streamflow prediction considering the influence of reservoirs in India.
Camille Labrousse, Wolfgang Ludwig, Sébastien Pinel, Mahrez Sadaoui, Andrea Toreti, and Guillaume Lacquement
Hydrol. Earth Syst. Sci., 26, 6055–6071, https://doi.org/10.5194/hess-26-6055-2022, https://doi.org/10.5194/hess-26-6055-2022, 2022
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The interest of this study is to demonstrate that we identify two zones in our study area whose hydroclimatic behaviours are uneven. By investigating relationships between the hydroclimatic conditions in both clusters for past observations with the overall atmospheric functioning, we show that the inequalities are mainly driven by a different control of the atmospheric teleconnection patterns over the area.
Daeha Kim, Minha Choi, and Jong Ahn Chun
Hydrol. Earth Syst. Sci., 26, 5955–5969, https://doi.org/10.5194/hess-26-5955-2022, https://doi.org/10.5194/hess-26-5955-2022, 2022
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We proposed a practical method that predicts the evaporation rates on land surfaces (ET) where only atmospheric data are available. Using a traditional equation that describes partitioning of precipitation into ET and streamflow, we could approximately identify the key parameter of the predicting formulation based on land–atmosphere interactions. The simple method conditioned by local climates outperformed sophisticated models in reproducing water-balance estimates across Australia.
Ruksana H. Rimi, Karsten Haustein, Emily J. Barbour, Sarah N. Sparrow, Sihan Li, David C. H. Wallom, and Myles R. Allen
Hydrol. Earth Syst. Sci., 26, 5737–5756, https://doi.org/10.5194/hess-26-5737-2022, https://doi.org/10.5194/hess-26-5737-2022, 2022
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Extreme rainfall events are major concerns in Bangladesh. Heavy downpours can cause flash floods and damage nearly harvestable crops in pre-monsoon season. While in monsoon season, the impacts can range from widespread agricultural loss, huge property damage, to loss of lives and livelihoods. This paper assesses the role of anthropogenic climate change drivers in changing risks of extreme rainfall events during pre-monsoon and monsoon seasons at local sub-regional-scale within Bangladesh.
Brigitta Simon-Gáspár, Gábor Soós, and Angela Anda
Hydrol. Earth Syst. Sci., 26, 4741–4756, https://doi.org/10.5194/hess-26-4741-2022, https://doi.org/10.5194/hess-26-4741-2022, 2022
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Due to climate change, it is extremely important to determine evaporation as accurately as possible. In nature, there are sediments and macrophytes in the open waters; thus, one of the aims was to investigate their effect on evaporation. The second aim of this paper was to estimate daily evaporation by using different models, which, according to results, have high priority in the evaporation prediction. Water management can obtain useful information from the results of the current research.
Haiyang Shi, Geping Luo, Olaf Hellwich, Mingjuan Xie, Chen Zhang, Yu Zhang, Yuangang Wang, Xiuliang Yuan, Xiaofei Ma, Wenqiang Zhang, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 26, 4603–4618, https://doi.org/10.5194/hess-26-4603-2022, https://doi.org/10.5194/hess-26-4603-2022, 2022
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There have been many machine learning simulation studies based on eddy-covariance observations for water flux and evapotranspiration. We performed a meta-analysis of such studies to clarify the impact of different algorithms and predictors, etc., on the reported prediction accuracy. It can, to some extent, guide future global water flux modeling studies and help us better understand the terrestrial ecosystem water cycle.
Yaozhi Jiang, Kun Yang, Hua Yang, Hui Lu, Yingying Chen, Xu Zhou, Jing Sun, Yuan Yang, and Yan Wang
Hydrol. Earth Syst. Sci., 26, 4587–4601, https://doi.org/10.5194/hess-26-4587-2022, https://doi.org/10.5194/hess-26-4587-2022, 2022
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Our study quantified the altitudinal precipitation gradients (PGs) over the Third Pole (TP). Most sub-basins in the TP have positive PGs, and negative PGs are found in the Himalayas, the Hengduan Mountains and the western Kunlun. PGs are positively correlated with wind speed but negatively correlated with relative humidity. In addition, PGs tend to be positive at smaller spatial scales compared to those at larger scales. The findings can assist precipitation interpolation in the data-sparse TP.
Kyungmin Sung, Max Carl Arne Torbenson, and James H. Stagge
EGUsphere, https://doi.org/10.5194/egusphere-2022-476, https://doi.org/10.5194/egusphere-2022-476, 2022
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This study is aims to analyze seasonal and long-term trend of meteorological drought trends under climate change. We merge tree-ring proxy with instrumental datasets to understand multi-centennial trends. We develop an approach for temporal downscaling from bi-annual time series to monthly scale, and develop a model for bias correction and trend analysis across all datasets. The model was applied to 14 sites in US, and found regions with recent wetting/drying trends and rapid seasonal shifts.
Francesca Carletti, Adrien Michel, Francesca Casale, Alice Burri, Daniele Bocchiola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 26, 3447–3475, https://doi.org/10.5194/hess-26-3447-2022, https://doi.org/10.5194/hess-26-3447-2022, 2022
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High Alpine catchments are dominated by the melting of seasonal snow cover and glaciers, whose amount and seasonality are expected to be modified by climate change. This paper compares the performances of different types of models in reproducing discharge among two catchments under present conditions and climate change. Despite many advantages, the use of simpler models for climate change applications is controversial as they do not fully represent the physics of the involved processes.
Ivan Vorobevskii, Thi Thanh Luong, Rico Kronenberg, Thomas Grünwald, and Christian Bernhofer
Hydrol. Earth Syst. Sci., 26, 3177–3239, https://doi.org/10.5194/hess-26-3177-2022, https://doi.org/10.5194/hess-26-3177-2022, 2022
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In the study we analysed the uncertainties of the meteorological data and model parameterization for evaporation modelling. We have taken a physically based lumped BROOK90 model and applied it in three different frameworks using global, regional and local datasets. Validating the simulations with eddy-covariance data from five stations in Germany, we found that the accuracy model parameterization plays a bigger role than the quality of the meteorological forcing.
Thomas Lees, Steven Reece, Frederik Kratzert, Daniel Klotz, Martin Gauch, Jens De Bruijn, Reetik Kumar Sahu, Peter Greve, Louise Slater, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 26, 3079–3101, https://doi.org/10.5194/hess-26-3079-2022, https://doi.org/10.5194/hess-26-3079-2022, 2022
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Despite the accuracy of deep learning rainfall-runoff models, we are currently uncertain of what these models have learned. In this study we explore the internals of one deep learning architecture and demonstrate that the model learns about intermediate hydrological stores of soil moisture and snow water, despite never having seen data about these processes during training. Therefore, we find evidence that the deep learning approach learns a physically realistic mapping from inputs to outputs.
Huajin Lei, Hongyu Zhao, and Tianqi Ao
Hydrol. Earth Syst. Sci., 26, 2969–2995, https://doi.org/10.5194/hess-26-2969-2022, https://doi.org/10.5194/hess-26-2969-2022, 2022
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How to combine multi-source precipitation data effectively is one of the hot topics in hydrometeorological research. This study presents a two-step merging strategy based on machine learning for multi-source precipitation merging over China. The results demonstrate that the proposed method effectively distinguishes the occurrence of precipitation events and reduces the error in precipitation estimation. This method is robust and may be successfully applied to other areas even with scarce data.
Alexane Lovat, Béatrice Vincendon, and Véronique Ducrocq
Hydrol. Earth Syst. Sci., 26, 2697–2714, https://doi.org/10.5194/hess-26-2697-2022, https://doi.org/10.5194/hess-26-2697-2022, 2022
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The hydrometeorological skills of two new nowcasting systems for forecasting Mediterranean intense rainfall events and floods are investigated. The results reveal that up to 75 or 90 min of forecast the performance of the nowcasting system blending numerical weather prediction and extrapolation of radar estimation is higher than the numerical weather model. For lead times up to 3 h the skills are equivalent in general. Using these nowcasting systems for flash flood forecasting is also promising.
Alexandre Tuel, Bettina Schaefli, Jakob Zscheischler, and Olivia Martius
Hydrol. Earth Syst. Sci., 26, 2649–2669, https://doi.org/10.5194/hess-26-2649-2022, https://doi.org/10.5194/hess-26-2649-2022, 2022
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River discharge is strongly influenced by the temporal structure of precipitation. Here, we show how extreme precipitation events that occur a few days or weeks after a previous event have a larger effect on river discharge than events occurring in isolation. Windows of 2 weeks or less between events have the most impact. Similarly, periods of persistent high discharge tend to be associated with the occurrence of several extreme precipitation events in close succession.
Hanieh Seyedhashemi, Jean-Philippe Vidal, Jacob S. Diamond, Dominique Thiéry, Céline Monteil, Frédéric Hendrickx, Anthony Maire, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 2583–2603, https://doi.org/10.5194/hess-26-2583-2022, https://doi.org/10.5194/hess-26-2583-2022, 2022
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Stream temperature appears to be increasing globally, but its rate remains poorly constrained due to a paucity of long-term data. Using a thermal model, this study provides a large-scale understanding of the evolution of stream temperature over a long period (1963–2019). This research highlights that air temperature and streamflow can exert joint influence on stream temperature trends, and riparian shading in small mountainous streams may mitigate warming in stream temperatures.
Shakirudeen Lawal, Stephen Sitch, Danica Lombardozzi, Julia E. M. S. Nabel, Hao-Wei Wey, Pierre Friedlingstein, Hanqin Tian, and Bruce Hewitson
Hydrol. Earth Syst. Sci., 26, 2045–2071, https://doi.org/10.5194/hess-26-2045-2022, https://doi.org/10.5194/hess-26-2045-2022, 2022
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To investigate the impacts of drought on vegetation, which few studies have done due to various limitations, we used the leaf area index as proxy and dynamic global vegetation models (DGVMs) to simulate drought impacts because the models use observationally derived climate. We found that the semi-desert biome responds strongly to drought in the summer season, while the tropical forest biome shows a weak response. This study could help target areas to improve drought monitoring and simulation.
Yubo Liu, Monica Garcia, Chi Zhang, and Qiuhong Tang
Hydrol. Earth Syst. Sci., 26, 1925–1936, https://doi.org/10.5194/hess-26-1925-2022, https://doi.org/10.5194/hess-26-1925-2022, 2022
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Our findings indicate that the reduction in contribution to the Iberian Peninsula (IP) summer precipitation is mainly concentrated in the IP and its neighboring grids. Compared with 1980–1997, both local recycling and external moisture were reduced during 1998–2019. The reduction in local recycling in the IP closely links to the disappearance of the wet years and the decreasing contribution in the dry years.
Nejc Bezak, Pasquale Borrelli, and Panos Panagos
Hydrol. Earth Syst. Sci., 26, 1907–1924, https://doi.org/10.5194/hess-26-1907-2022, https://doi.org/10.5194/hess-26-1907-2022, 2022
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Rainfall erosivity is one of the main factors in soil erosion. A satellite-based global map of rainfall erosivity was constructed using data with a 30 min time interval. It was shown that the satellite-based precipitation products are an interesting option for estimating rainfall erosivity, especially in regions with limited ground data. However, ground-based high-frequency precipitation measurements are (still) essential for accurate estimates of rainfall erosivity.
Xueli Yang, Zhi-Hua Wang, and Chenghao Wang
Hydrol. Earth Syst. Sci., 26, 1845–1856, https://doi.org/10.5194/hess-26-1845-2022, https://doi.org/10.5194/hess-26-1845-2022, 2022
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In this study, we investigated potentially catastrophic transitions in hydrological processes by identifying the early-warning signals which manifest as a
critical slowing downin complex dynamic systems. We then analyzed the precipitation network of cities in the contiguous United States and found that key network parameters, such as the nodal density and the clustering coefficient, exhibit similar dynamic behaviour, which can serve as novel early-warning signals for the hydrological system.
Zhuoyi Tu, Yuting Yang, and Michael L. Roderick
Hydrol. Earth Syst. Sci., 26, 1745–1754, https://doi.org/10.5194/hess-26-1745-2022, https://doi.org/10.5194/hess-26-1745-2022, 2022
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Here we test a maximum evaporation theory that acknowledges the interdependence between radiation, surface temperature, and evaporation over saturated land. We show that the maximum evaporation approach recovers observed evaporation and surface temperature under non-water-limited conditions across a broad range of bio-climates. The implication is that the maximum evaporation concept can be used to predict potential evaporation that has long been a major difficulty for the hydrological community.
Cited articles
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