Articles | Volume 16, issue 2
https://doi.org/10.5194/gmd-16-557-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-557-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
25 Jan 2023
Model description paper |
| 25 Jan 2023
| 25 Jan 2023
stoPET v1.0: a stochastic potential evapotranspiration generator for simulation of climate change impacts
Dagmawi Teklu Asfaw
CORRESPONDING AUTHOR
School of Geographical Sciences, University of Bristol, Bristol, UK
Michael Bliss Singer
School of Earth and Environmental Sciences, Cardiff University,
Cardiff, UK
Water Research Institute, Cardiff University, Cardiff, UK
Earth Research Institute, University of California Santa Barbara,
Santa Barbara, USA
Rafael Rosolem
Department of Civil Engineering, University of Bristol, Bristol, UK
Cabot Institute for the Environment, University of Bristol, Bristol, UK
David MacLeod
School of Geographical Sciences, University of Bristol, Bristol, UK
Mark Cuthbert
School of Earth and Environmental Sciences, Cardiff University,
Cardiff, UK
School of Civil and Environmental Engineering, University of New South Wales (UNSW), Sydney, Australia
Edisson Quichimbo Miguitama
School of Earth and Environmental Sciences, Cardiff University,
Cardiff, UK
Manuel F. Rios Gaona
School of Earth and Environmental Sciences, Cardiff University,
Cardiff, UK
Katerina Michaelides
School of Geographical Sciences, University of Bristol, Bristol, UK
Earth Research Institute, University of California Santa Barbara,
Santa Barbara, USA
Cabot Institute for the Environment, University of Bristol, Bristol, UK
Related authors
Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data, 15, 5449–5466, https://doi.org/10.5194/essd-15-5449-2023, https://doi.org/10.5194/essd-15-5449-2023, 2023
Short summary
Short summary
Drought is undeniably one of the most intricate and significant natural hazards with far-reaching consequences for the environment, economy, water resources, agriculture, and societies across the globe. In response to this challenge, we have devised high-resolution drought indices. These indices serve as invaluable indicators for assessing shifts in drought patterns and their associated impacts on a global, regional, and local level facilitating the development of tailored adaptation strategies.
Saskia Salwey, Gemma Coxon, Francesca Pianosi, Rosanna Lane, Chris Hutton, Michael Bliss Singer, Hilary McMillan, and Jim Freer
EGUsphere, https://doi.org/10.5194/egusphere-2024-326, https://doi.org/10.5194/egusphere-2024-326, 2024
Short summary
Short summary
Reservoirs are essential for water resource management and can significantly impact downstream flow. However, representing reservoirs in hydrological models can be challenging, particularly across large-scales. We design a new, simple method for simulating river flow downstream of water supply reservoirs using only open-access data. We demonstrate the approach in 264 reservoir catchments across Great Britain where we can significantly improve the simulation of reservoir-impacted flow.
Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data, 15, 5449–5466, https://doi.org/10.5194/essd-15-5449-2023, https://doi.org/10.5194/essd-15-5449-2023, 2023
Short summary
Short summary
Drought is undeniably one of the most intricate and significant natural hazards with far-reaching consequences for the environment, economy, water resources, agriculture, and societies across the globe. In response to this challenge, we have devised high-resolution drought indices. These indices serve as invaluable indicators for assessing shifts in drought patterns and their associated impacts on a global, regional, and local level facilitating the development of tailored adaptation strategies.
Yanchen Zheng, Gemma Coxon, Ross Woods, Daniel Power, Miguel Angel Rico-Ramirez, David McJannet, Rafael Rosolem, Jianzhu Li, and Ping Feng
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-224, https://doi.org/10.5194/hess-2023-224, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
Reanalysis soil moisture products are vital basis for hydrological and environmental research. Previous products evaluation is limited by the scale difference (point and grid scale). This paper adopts Cosmic Ray Neutron Sensors (CRNS) observations, a novel technique that provide root-zone soil moisture at field scale. In this paper, global harmonized CRNS observations was used to assess products. Overall, ERA5-Land, CFSv2, CRA40, GLEAM show better performance than MERRA2, GLDAS-Noah and JRA55.
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
EGUsphere, https://doi.org/10.5194/egusphere-2023-1548, https://doi.org/10.5194/egusphere-2023-1548, 2023
Short summary
Short summary
This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within mHM, using the Desilets equation with uniformly and with non-uniformly weighted average soil moisture, and the physically-based code COSMIC. The data not only improved soil moisture simulations, but also the parameterization of evapotranspiration in the model.
Manuel Felipe Rios Gaona, Katerina Michaelides, and Michael Bliss Singer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-98, https://doi.org/10.5194/gmd-2023-98, 2023
Revised manuscript under review for GMD
Short summary
Short summary
STORM v.2 (short for STOchastic Rainfall Model version 2.0) is an open-source, and user-friendly modeling framework for simulating rainfall fields over a basin. It also allows simulating the impact of plausible climate change either on the total seasonal rainfall or the storm’s maximum intensity.
Shiuan-An Chen, Katerina Michaelides, David A. Richards, and Michael Bliss Singer
Earth Surf. Dynam., 10, 1055–1078, https://doi.org/10.5194/esurf-10-1055-2022, https://doi.org/10.5194/esurf-10-1055-2022, 2022
Short summary
Short summary
Drainage basin erosion rates influence landscape evolution through controlling land surface lowering and sediment flux, but gaps remain in understanding their large-scale patterns and drivers between timescales. We analysed global erosion rates and show that long-term erosion rates are controlled by rainfall, former glacial processes, and basin landform, whilst human activities enhance short-term erosion rates. The results highlight the complex interplay of controls on land surface processes.
William Rust, John P. Bloomfield, Mark Cuthbert, Ron Corstanje, and Ian Holman
Hydrol. Earth Syst. Sci., 26, 2449–2467, https://doi.org/10.5194/hess-26-2449-2022, https://doi.org/10.5194/hess-26-2449-2022, 2022
Short summary
Short summary
We highlight the importance of the North Atlantic Oscillation in controlling droughts in the UK. Specifically, multi-year cycles in the NAO are shown to influence the frequency of droughts and this influence changes considerably over time. We show that the influence of these varying controls is similar to the projected effects of climate change on water resources. We also show that these time-varying behaviours have important implications for water resource forecasts used for drought planning.
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, https://doi.org/10.5194/essd-14-1125-2022, 2022
Short summary
Short summary
Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Shaini Naha, Miguel Angel Rico-Ramirez, and Rafael Rosolem
Hydrol. Earth Syst. Sci., 25, 6339–6357, https://doi.org/10.5194/hess-25-6339-2021, https://doi.org/10.5194/hess-25-6339-2021, 2021
Short summary
Short summary
Rapid growth in population in developing countries leads to an increase in food demand, and as a consequence, percentages of land are being converted to cropland which alters river flow processes. This study describes how the hydrology of a flood-prone river basin in India would respond to the current and future changes in land cover. Our findings indicate that the recurrent flood events occurring in the basin might be influenced by these changes in land cover at the catchment scale.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, https://doi.org/10.5194/gmd-14-7545-2021, 2021
Short summary
Short summary
Groundwater is increasingly being included in large-scale (continental to global) land surface and hydrologic simulations. However, it is challenging to evaluate these simulations because groundwater is
hiddenunderground and thus hard to measure. We suggest using multiple complementary strategies to assess the performance of a model (
model evaluation).
Daniel Power, Miguel Angel Rico-Ramirez, Sharon Desilets, Darin Desilets, and Rafael Rosolem
Geosci. Model Dev., 14, 7287–7307, https://doi.org/10.5194/gmd-14-7287-2021, https://doi.org/10.5194/gmd-14-7287-2021, 2021
Short summary
Short summary
Cosmic-ray neutron sensors estimate root-zone soil moisture at sub-kilometre scales. There are national-scale networks of these sensors across the globe; however, methods for converting neutron signals to soil moisture values are inconsistent. This paper describes our open-source Python tool that processes raw sensor data into soil moisture estimates. The aim is to allow a user to ensure they have a harmonized data set, along with informative metadata, to facilitate both research and teaching.
E. Andrés Quichimbo, Michael Bliss Singer, Katerina Michaelides, Daniel E. J. Hobley, Rafael Rosolem, and Mark O. Cuthbert
Geosci. Model Dev., 14, 6893–6917, https://doi.org/10.5194/gmd-14-6893-2021, https://doi.org/10.5194/gmd-14-6893-2021, 2021
Short summary
Short summary
Understanding and quantifying water partitioning in dryland regions are of key importance to anticipate the future impacts of climate change in water resources and dryland ecosystems. Here, we have developed a simple hydrological model (DRYP) that incorporates the key processes of water partitioning in drylands. DRYP is a modular, versatile, and parsimonious model that can be used to anticipate and plan for climatic and anthropogenic changes to water fluxes and storage in dryland regions.
Maria Magdalena Warter, Michael Bliss Singer, Mark O. Cuthbert, Dar Roberts, Kelly K. Caylor, Romy Sabathier, and John Stella
Hydrol. Earth Syst. Sci., 25, 3713–3729, https://doi.org/10.5194/hess-25-3713-2021, https://doi.org/10.5194/hess-25-3713-2021, 2021
Short summary
Short summary
Intensified drying of soil and grassland vegetation is raising the impact of fire severity and extent in Southern California. While browned grassland is a common sight during the dry season, this study has shown that there is a pronounced shift in the timing of senescence, due to changing climate conditions favoring milder winter temperatures and increased precipitation variability. Vegetation may be limited in its ability to adapt to these shifts, as drought periods become more frequent.
William Rust, Mark Cuthbert, John Bloomfield, Ron Corstanje, Nicholas Howden, and Ian Holman
Hydrol. Earth Syst. Sci., 25, 2223–2237, https://doi.org/10.5194/hess-25-2223-2021, https://doi.org/10.5194/hess-25-2223-2021, 2021
Short summary
Short summary
In this paper, we find evidence for the cyclical behaviour (on a 7-year basis) in UK streamflow records that match the main cycle of the North Atlantic Oscillation. Furthermore, we find that the strength of these 7-year cycles in streamflow is dependent on proportional contributions from groundwater and the response times of the underlying groundwater systems. This may allow for improvements to water management practices through better understanding of long-term streamflow behaviour.
Isaac Kipkemoi, Katerina Michaelides, Rafael Rosolem, and Michael Bliss Singer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-48, https://doi.org/10.5194/hess-2021-48, 2021
Manuscript not accepted for further review
Short summary
Short summary
The work is a novel investigation of the role of temporal rainfall resolution and intensity in affecting the water balance of soil in a dryland environment. This research has implications for what rainfall data are used to assess the impact of climate and climate change on the regional water balance. This information is critical for anticipating the impact of a changing climate on dryland communities globally who need it to know when to plant their seeds or where livestock pasture is available.
David MacLeod, Mary Kilavi, Emmah Mwangi, Maurine Ambani, Michael Osunga, Joanne Robbins, Richard Graham, Pedram Rowhani, and Martin C. Todd
Nat. Hazards Earth Syst. Sci., 21, 261–277, https://doi.org/10.5194/nhess-21-261-2021, https://doi.org/10.5194/nhess-21-261-2021, 2021
Short summary
Short summary
Forecasts of natural hazards save lives. But the accuracy of forecasts must be evaluated before use. Here we evaluate heavy rainfall advisories over Kenya. We assess their ability to anticipate heavy rainfall and show how well they warned of recent floods which had significant impacts. We find that although they effectively warn of heavy rainfall and flooding, issues such as a lack of spatial detail limit their utility for systematic approaches to preparedness.
Gabriel C. Rau, Mark O. Cuthbert, R. Ian Acworth, and Philipp Blum
Hydrol. Earth Syst. Sci., 24, 6033–6046, https://doi.org/10.5194/hess-24-6033-2020, https://doi.org/10.5194/hess-24-6033-2020, 2020
Short summary
Short summary
This work provides an important generalisation of a previously developed method that quantifies subsurface barometric efficiency using the groundwater level response to Earth and atmospheric tides. The new approach additionally allows the quantification of hydraulic conductivity and specific storage. This enables improved and rapid assessment of subsurface processes and properties using standard pressure measurements.
Simon Opie, Richard G. Taylor, Chris M. Brierley, Mohammad Shamsudduha, and Mark O. Cuthbert
Earth Syst. Dynam., 11, 775–791, https://doi.org/10.5194/esd-11-775-2020, https://doi.org/10.5194/esd-11-775-2020, 2020
Short summary
Short summary
Knowledge of the relationship between climate and groundwater is limited and typically undermined by the scale, duration and accessibility of observations. Using monthly satellite measurements newly compiled over 14 years in the tropics and sub-tropics, we show that the imprint of precipitation history on groundwater, i.e. hydraulic memory, is longer in drylands than humid environments with important implications for the understanding and management of groundwater resources under climate change.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-378, https://doi.org/10.5194/hess-2020-378, 2020
Revised manuscript not accepted
Shaini Naha, Miguel A. Rico-Ramirez, and Rafael Rosolem
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-220, https://doi.org/10.5194/hess-2020-220, 2020
Manuscript not accepted for further review
Short summary
Short summary
Rapid growth in population in developing countries leads to an increase in food demand and as a consequence, percentages of land are being converted to cropland which alters the river flow processes. Therefore we try to understand the exact role of these changes in modifying the river flows through the prediction of the impacts of these changes in the future by taking a clue from the past. This study concludes that recurrent flood events might be influenced by these changes in future.
Romane Berthelin, Michael Rinderer, Bartolomé Andreo, Andy Baker, Daniela Kilian, Gabriele Leonhardt, Annette Lotz, Kurt Lichtenwoehrer, Matías Mudarra, Ingrid Y. Padilla, Fernando Pantoja Agreda, Rafael Rosolem, Abel Vale, and Andreas Hartmann
Geosci. Instrum. Method. Data Syst., 9, 11–23, https://doi.org/10.5194/gi-9-11-2020, https://doi.org/10.5194/gi-9-11-2020, 2020
Short summary
Short summary
We present the setup of a soil moisture monitoring network, which is implemented at five karstic sites with different climates across the globe. More than 400 soil moisture probes operating at a high spatio-temporal resolution will improve the understanding of groundwater recharge and evapotranspiration processes in karstic areas.
William Rust, Ian Holman, John Bloomfield, Mark Cuthbert, and Ron Corstanje
Hydrol. Earth Syst. Sci., 23, 3233–3245, https://doi.org/10.5194/hess-23-3233-2019, https://doi.org/10.5194/hess-23-3233-2019, 2019
Short summary
Short summary
We show that major groundwater resources in the UK exhibit strong multi-year cycles, accounting for up to 40 % of total groundwater level variability. By comparing these cycles with recorded widespread groundwater droughts over the past 60 years, we provide evidence that climatic systems (such as the North Atlantic Oscillation) ultimately drive drought-risk periods in UK groundwater. The recursive nature of these drought-risk periods may lead to improved preparedness for future droughts.
Kristian Strommen, Hannah M. Christensen, Dave MacLeod, Stephan Juricke, and Tim N. Palmer
Geosci. Model Dev., 12, 3099–3118, https://doi.org/10.5194/gmd-12-3099-2019, https://doi.org/10.5194/gmd-12-3099-2019, 2019
Short summary
Short summary
Due to computational limitations, climate models cannot fully resolve the laws of physics below a certain scale – a large source of errors and uncertainty. Stochastic schemes aim to account for this by randomly sampling the possible unresolved states. We develop new stochastic schemes for the EC-Earth climate model and evaluate their impact on model performance. While several benefits are found, the impact is sometimes too strong, suggesting such schemes must be carefully calibrated before use.
Seshagiri Rao Kolusu, Mohammad Shamsudduha, Martin C. Todd, Richard G. Taylor, David Seddon, Japhet J. Kashaigili, Girma Y. Ebrahim, Mark O. Cuthbert, James P. R. Sorensen, Karen G. Villholth, Alan M. MacDonald, and Dave A. MacLeod
Hydrol. Earth Syst. Sci., 23, 1751–1762, https://doi.org/10.5194/hess-23-1751-2019, https://doi.org/10.5194/hess-23-1751-2019, 2019
Thomas Turpin-Jelfs, Katerina Michaelides, Joel A. Biederman, and Alexandre M. Anesio
Biogeosciences, 16, 369–381, https://doi.org/10.5194/bg-16-369-2019, https://doi.org/10.5194/bg-16-369-2019, 2019
Short summary
Short summary
Increasing shrub cover promotes land degradation in semi-arid grasslands and has the potential to impact the soil nitrogen pool, which is essential to primary production. Our study showed that increasing shrub cover concentrates soil nitrogen into localised patches beneath shrub canopies. Further, we determined that increasing shrub cover inhibits inputs of nitrogen by the soil microbial community. Thus, we conclude this phenomenon can perturb nitrogen cycling in these ecosystems.
Fanny Sarrazin, Andreas Hartmann, Francesca Pianosi, Rafael Rosolem, and Thorsten Wagener
Geosci. Model Dev., 11, 4933–4964, https://doi.org/10.5194/gmd-11-4933-2018, https://doi.org/10.5194/gmd-11-4933-2018, 2018
Short summary
Short summary
We propose the first large-scale vegetation–recharge model for karst regions (V2Karst), which enables the analysis of the impact of changes in climate and land cover on karst groundwater recharge. We demonstrate the plausibility of V2Karst simulations against observations at FLUXNET sites and of controlling modelled processes using sensitivity analysis. We perform virtual experiments to further test the model and gain insight into its sensitivity to precipitation pattern and vegetation cover.
Michael Bliss Singer, Katerina Michaelides, and Daniel E. J. Hobley
Geosci. Model Dev., 11, 3713–3726, https://doi.org/10.5194/gmd-11-3713-2018, https://doi.org/10.5194/gmd-11-3713-2018, 2018
Short summary
Short summary
For various applications, a regional or local characterization of rainfall is required, particularly at the watershed scale, where there is spatial heterogeneity. Furthermore, simple models are needed that can simulate various scenarios of climate change including changes in seasonal wetness and rainstorm intensity. To this end, we have developed the STOchastic Rainstorm Model (STORM). We explain its developments and data requirements, and illustrate how it simulates rainstorms over a basin.
Manuel F. Rios Gaona, Aart Overeem, Timothy H. Raupach, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 11, 4465–4476, https://doi.org/10.5194/amt-11-4465-2018, https://doi.org/10.5194/amt-11-4465-2018, 2018
Short summary
Short summary
Rainfall estimates from commercial microwave links were obtained for the city of Sao Paulo (Brazil). The results show the potential of such networks as complementary rainfall measurements for more robust networks (e.g. radars, gauges, satellites).
Martin Schrön, Markus Köhli, Lena Scheiffele, Joost Iwema, Heye R. Bogena, Ling Lv, Edoardo Martini, Gabriele Baroni, Rafael Rosolem, Jannis Weimar, Juliane Mai, Matthias Cuntz, Corinna Rebmann, Sascha E. Oswald, Peter Dietrich, Ulrich Schmidt, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, https://doi.org/10.5194/hess-21-5009-2017, 2017
Short summary
Short summary
A field-scale average of near-surface water content can be sensed by cosmic-ray neutron detectors. To interpret, calibrate, and validate the integral signal, it is important to account for its sensitivity to heterogeneous patterns like dry or wet spots. We show how point samples contribute to the neutron signal based on their depth and distance from the detector. This approach robustly improves the sensor performance and data consistency, and even reveals otherwise hidden hydrological features.
Joost Iwema, Rafael Rosolem, Mostaquimur Rahman, Eleanor Blyth, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 21, 2843–2861, https://doi.org/10.5194/hess-21-2843-2017, https://doi.org/10.5194/hess-21-2843-2017, 2017
Short summary
Short summary
We investigated whether the simulation of water flux from the land surface to the atmosphere (using the Joint UK Land Environment Simulator model) could be improved by replacing traditional soil moisture sensor data with data from the more novel Cosmic-Ray Neutron soil moisture sensor. Despite observed differences between the two types of soil moisture measurement data, we found no substantial differences in improvement in water flux estimation, based on multiple calibration experiments.
Mostaquimur Rahman and Rafael Rosolem
Hydrol. Earth Syst. Sci., 21, 459–471, https://doi.org/10.5194/hess-21-459-2017, https://doi.org/10.5194/hess-21-459-2017, 2017
Short summary
Short summary
Modelling water flow through chalk (a fine-grained porous medium traversed by fractures) is important for optimizing water resource management practices in the UK. However, efficient simulations of water movement through chalk are difficult due to the porous nature of chalk, creating high-velocity preferential flow paths. This paper describes a novel approach to representing chalk hydrology in land surface modelling for large-scale applications.
Dave MacLeod, Hannah Cloke, Florian Pappenberger, and Antje Weisheimer
Hydrol. Earth Syst. Sci., 20, 2737–2743, https://doi.org/10.5194/hess-20-2737-2016, https://doi.org/10.5194/hess-20-2737-2016, 2016
Short summary
Short summary
Soil moisture memory is a key aspect of seasonal climate predictions, through feedback between the land surface and the atmosphere. Estimates have been made of the length of soil moisture memory; however, we show here how estimates of memory show large variation with uncertain model parameters. Explicit representation of model uncertainty may then improve the realism of simulations and seasonal climate forecasts.
C. E. M. Lloyd, K. Michaelides, D. R. Chadwick, J. A. J. Dungait, and R. P. Evershed
Biogeosciences, 13, 551–566, https://doi.org/10.5194/bg-13-551-2016, https://doi.org/10.5194/bg-13-551-2016, 2016
Short summary
Short summary
Our interdisciplinary research brings together methodologies from hydrology, soil science and biogeochemistry to address key questions about the transport of cattle slurry in the environment. The paper provides a novel approach to trace dissolved and particulate components of cattle slurry through an experimental hillslope system. This work provides one of the first examples of using biomarkers to assess the effects of slope gradient and rainfall intensity on the movement of slurry derived-OM.
A. F. Charteris, T. D. J. Knowles, K. Michaelides, and R. P. Evershed
SOIL Discuss., https://doi.org/10.5194/soild-2-1135-2015, https://doi.org/10.5194/soild-2-1135-2015, 2015
Manuscript not accepted for further review
X. Han, X. Li, G. He, P. Kumbhar, C. Montzka, S. Kollet, T. Miyoshi, R. Rosolem, Y. Zhang, H. Vereecken, and H.-J. H. Franssen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-8-7395-2015, https://doi.org/10.5194/gmdd-8-7395-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
DasPy is a ready to use open source parallel multivariate land data assimilation framework with joint state and parameter estimation using Local Ensemble Transform Kalman Filter. The Community Land Model (4.5) was integrated as model operator. The Community Microwave Emission Modelling platform, COsmic-ray Soil Moisture Interaction Code and the Two-Source Formulation were integrated as observation operators for the multivariate assimilation of soil moisture and soil temperature, respectively.
M. F. Rios Gaona, A. Overeem, H. Leijnse, and R. Uijlenhoet
Hydrol. Earth Syst. Sci., 19, 3571–3584, https://doi.org/10.5194/hess-19-3571-2015, https://doi.org/10.5194/hess-19-3571-2015, 2015
Short summary
Short summary
Commercial cellular networks are built for telecommunication purposes. These kinds of networks have lately been used to obtain rainfall maps at country-wide scales. From previous studies, we now quantify the uncertainties associated with such maps. To do so, we divided the sources or error into two categories: from microwave link measurements and from mapping. It was found that the former is the source that contributes the most to the overall error in rainfall maps from microwave link network.
J. Iwema, R. Rosolem, R. Baatz, T. Wagener, and H. R. Bogena
Hydrol. Earth Syst. Sci., 19, 3203–3216, https://doi.org/10.5194/hess-19-3203-2015, https://doi.org/10.5194/hess-19-3203-2015, 2015
Short summary
Short summary
The cosmic-ray neutron sensor can provide soil moisture content averages over areas of roughly half a kilometre by half a kilometre. Although this sensor is usually calibrated using soil samples taken on a single day, we found that multiple sampling days are needed. The calibration results were also affected by the soil wetness conditions of the sampling days. The outcome of this study will help researchers to calibrate/validate new cosmic-ray neutron sensor sites more accurately.
P. T. S. Oliveira, E. Wendland, M. A. Nearing, R. L. Scott, R. Rosolem, and H. R. da Rocha
Hydrol. Earth Syst. Sci., 19, 2899–2910, https://doi.org/10.5194/hess-19-2899-2015, https://doi.org/10.5194/hess-19-2899-2015, 2015
Short summary
Short summary
We determined the main components of the water balance for an undisturbed cerrado.
Evapotranspiration ranged from 1.91 to 2.60mm per day for the dry and wet seasons, respectively. Canopy interception ranged from 4 to 20% and stemflow values were approximately 1% of gross precipitation.
The average runoff coefficient was less than 1%, while cerrado deforestation has the potential to increase that amount up to 20-fold.
The water storage may be estimated by the difference between P and ET.
A. Hartmann, T. Gleeson, R. Rosolem, F. Pianosi, Y. Wada, and T. Wagener
Geosci. Model Dev., 8, 1729–1746, https://doi.org/10.5194/gmd-8-1729-2015, https://doi.org/10.5194/gmd-8-1729-2015, 2015
Short summary
Short summary
We present a new approach to assess karstic groundwater recharge over Europe and the Mediterranean. Cluster analysis is used to subdivide all karst regions into four typical karst landscapes and to simulate karst recharge with a process-based karst model. We estimate its parameters by a combination of a priori information and observations of soil moisture and evapotranspiration. Independent observations of recharge that present large-scale models significantly under-estimate karstic recharge.
X. Han, H.-J. H. Franssen, R. Rosolem, R. Jin, X. Li, and H. Vereecken
Hydrol. Earth Syst. Sci., 19, 615–629, https://doi.org/10.5194/hess-19-615-2015, https://doi.org/10.5194/hess-19-615-2015, 2015
Short summary
Short summary
This paper presents the joint assimilation of cosmic-ray neutron counts and land surface temperature with parameter estimation of leaf area index at an irrigated corn field. The results show that the data assimilation can reduce the systematic input errors due to the lack of irrigation data. The estimations of soil moisture, evapotranspiration and leaf area index can be improved in the joint assimilation framework.
R. Rosolem, T. Hoar, A. Arellano, J. L. Anderson, W. J. Shuttleworth, X. Zeng, and T. E. Franz
Hydrol. Earth Syst. Sci., 18, 4363–4379, https://doi.org/10.5194/hess-18-4363-2014, https://doi.org/10.5194/hess-18-4363-2014, 2014
J. Shuttleworth, R. Rosolem, M. Zreda, and T. Franz
Hydrol. Earth Syst. Sci., 17, 3205–3217, https://doi.org/10.5194/hess-17-3205-2013, https://doi.org/10.5194/hess-17-3205-2013, 2013
T. E. Franz, M. Zreda, R. Rosolem, and T. P. A. Ferre
Hydrol. Earth Syst. Sci., 17, 453–460, https://doi.org/10.5194/hess-17-453-2013, https://doi.org/10.5194/hess-17-453-2013, 2013
Related subject area
Climate and Earth system modeling
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
CD-type discretization for sea ice dynamics in FESOM version 2
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)
Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models
Evaluation and optimisation of the soil carbon turnover routine in the MONICA model (version 3.3.1)
Assessing the sensitivity of aerosol mass budget and effective radiative forcing to horizontal grid spacing in E3SMv1 using a regional refinement approach
Towards the definition of a solar forcing dataset for CMIP7
ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1)
Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region
Constraining the carbon cycle in JULES-ES-1.0
The utility of simulated ocean chlorophyll observations: a case study with the Chlorophyll Observation Simulator Package (version 1) in CESMv2.2
GeoPDNN 1.0: a semi-supervised deep learning neural network using pseudo-labels for three-dimensional shallow strata modelling and uncertainty analysis in urban areas from borehole data
The prototype NOAA Aerosol Reanalysis version 1.0: description of the modeling system and its evaluation
Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1
Monsoon Mission Coupled Forecast System version 2.0: model description and Indian monsoon simulations
Exploring the ocean mesoscale at reduced computational cost with FESOM 2.5: efficient modeling strategies applied to the Southern Ocean
Truly conserving with conservative remapping methods
High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia
Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rc
Global Downscaled Projections for Climate Impacts Research (GDPCIR): preserving quantile trends for modeling future climate impacts
Understanding changes in cloud simulations from E3SM version 1 to version 2
WRF (v4.0)–SUEWS (v2018c) coupled system: development, evaluation and application
Scenario setup and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a)
Deep learning model based on multi-scale feature fusion for precipitation nowcasting
The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change
Getting the leaves right matters for estimating temperature extremes
The Southern Ocean Freshwater Input from Antarctica (SOFIA) Initiative: scientific objectives and experimental design
Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization
The Regional Climate-Chemistry-Ecology Coupling Model RegCM-Chem (v4.6)-YIBs (v1.0): Development and Application
Process-oriented models of autumn leaf phenology: ways to sound calibration and implications of uncertain projections
An evaluation of the LLC4320 global-ocean simulation based on the submesoscale structure of modeled sea surface temperature fields
An emulation-based approach for interrogating reactive transport models
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
A sub-grid parameterization scheme for topographic vertical motion in CAM5-SE
Objective Evaluation of Earth System Models: PCMDI Metrics Package (PMP) version 3
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
Short summary
Short summary
This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
Short summary
Short summary
The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
Short summary
Short summary
This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
Short summary
Short summary
Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
Short summary
Short summary
Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
Short summary
Short summary
Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
Short summary
Short summary
This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
Short summary
Short summary
Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
Short summary
Short summary
Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
Short summary
Short summary
We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
Short summary
Short summary
Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
Short summary
Short summary
As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
Short summary
Short summary
In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
Short summary
Short summary
This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
Short summary
Short summary
A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
Short summary
Short summary
Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
Short summary
Short summary
Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
Short summary
Short summary
The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
Short summary
Short summary
We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
Short summary
Short summary
This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
Short summary
Short summary
By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
Short summary
Short summary
We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
Short summary
Short summary
Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
Short summary
Short summary
We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
Short summary
Short summary
We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
Short summary
Short summary
Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
Short summary
Short summary
This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
Short summary
Short summary
This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
Short summary
Short summary
The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Deepeshkumar Jain, Suryachandra A. Rao, Ramu A. Dandi, Prasanth A. Pillai, Ankur Srivastava, Maheswar Pradhan, and Kiran V. Gangadharan
Geosci. Model Dev., 17, 709–729, https://doi.org/10.5194/gmd-17-709-2024, https://doi.org/10.5194/gmd-17-709-2024, 2024
Short summary
Short summary
The present paper discusses and evaluates the new Monsoon Mission Coupled Forecast System model (MMCFS) version 2.0 which upgrades the currently operational MMCFS v1.0 at the Indian Meteorological Department, India. The individual model components have been substantially upgraded independently by their respective scientific groups. MMCFS v2.0 includes these upgrades in the operational coupled model. The new model shows significant skill improvement in simulating the Indian monsoon.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
Short summary
Short summary
Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Karl E. Taylor
Geosci. Model Dev., 17, 415–430, https://doi.org/10.5194/gmd-17-415-2024, https://doi.org/10.5194/gmd-17-415-2024, 2024
Short summary
Short summary
Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for some common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, and Angelina Bushenkova
Geosci. Model Dev., 17, 229–259, https://doi.org/10.5194/gmd-17-229-2024, https://doi.org/10.5194/gmd-17-229-2024, 2024
Short summary
Short summary
This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
Short summary
Short summary
We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere–ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Diana R. Gergel, Steven B. Malevich, Kelly E. McCusker, Emile Tenezakis, Michael T. Delgado, Meredith A. Fish, and Robert E. Kopp
Geosci. Model Dev., 17, 191–227, https://doi.org/10.5194/gmd-17-191-2024, https://doi.org/10.5194/gmd-17-191-2024, 2024
Short summary
Short summary
The freely available Global Downscaled Projections for Climate Impacts Research (GDPCIR) dataset gives researchers a new tool for studying how future climate will evolve at a local or regional level, corresponding to the latest global climate model simulations prepared as part of the UN Intergovernmental Panel on Climate Change’s Sixth Assessment Report. Those simulations represent an enormous advance in quality, detail, and scope that GDPCIR translates to the local level.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
Short summary
Short summary
We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev., 17, 91–116, https://doi.org/10.5194/gmd-17-91-2024, https://doi.org/10.5194/gmd-17-91-2024, 2024
Short summary
Short summary
For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
Short summary
Short summary
Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev., 17, 53–69, https://doi.org/10.5194/gmd-17-53-2024, https://doi.org/10.5194/gmd-17-53-2024, 2024
Short summary
Short summary
This study presents a deep learning architecture, multi-scale feature fusion (MFF), to improve the forecast skills of precipitations especially for heavy precipitations. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors so that heavy precipitations are produced.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
Short summary
Short summary
Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, https://doi.org/10.5194/gmd-16-7357-2023, 2023
Short summary
Short summary
Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
Short summary
Short summary
Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Geosci. Model Dev., 16, 7311–7337, https://doi.org/10.5194/gmd-16-7311-2023, https://doi.org/10.5194/gmd-16-7311-2023, 2023
Short summary
Short summary
Irrigation modifies the land surface and soil conditions. The effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which simulates the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in terms of their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Baiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
EGUsphere, https://doi.org/10.5194/egusphere-2023-1733, https://doi.org/10.5194/egusphere-2023-1733, 2023
Short summary
Short summary
For the first time, we coupled a regional climate chemistry model RegCM-Chem with a dynamic vegetation model YIBs to create a regional climate-chemistry-ecology model RegCM-Chem-YIBs. We applied it to simulate climatic, chemical and ecological parameters in East Asia and fully validated it on a variety of observational data. The research results show that RegCM-Chem-YIBs model is a valuable tool for studying terrestrial carbon cycle, atmospheric chemistry, and climate change in regional scale.
Michael Meier and Christof Bigler
Geosci. Model Dev., 16, 7171–7201, https://doi.org/10.5194/gmd-16-7171-2023, https://doi.org/10.5194/gmd-16-7171-2023, 2023
Short summary
Short summary
We analyzed >2.3 million calibrations and 39 million projections of leaf coloration models, considering 21 models, 5 optimization algorithms, ≥7 sampling procedures, and 26 climate scenarios. Models based on temperature, day length, and leaf unfolding performed best, especially when calibrated with generalized simulated annealing and systematically balanced or stratified samples. Projected leaf coloration shifts between −13 and +20 days by 2080–2099.
Katharina Gallmeier, J. Xavier Prochaska, Peter Cornillon, Dimitris Menemenlis, and Madolyn Kelm
Geosci. Model Dev., 16, 7143–7170, https://doi.org/10.5194/gmd-16-7143-2023, https://doi.org/10.5194/gmd-16-7143-2023, 2023
Short summary
Short summary
This paper introduces an approach to evaluate numerical models of ocean circulation. We compare the structure of satellite-derived sea surface temperature anomaly (SSTa) instances determined by a machine learning algorithm at 10–80 km scales to those output by a high-resolution MITgcm run. The simulation over much of the ocean reproduces the observed distribution of SSTa patterns well. This general agreement, alongside a few notable exceptions, highlights the potential of this approach.
Angus Fotherby, Harold J. Bradbury, Jennifer L. Druhan, and Alexandra V. Turchyn
Geosci. Model Dev., 16, 7059–7074, https://doi.org/10.5194/gmd-16-7059-2023, https://doi.org/10.5194/gmd-16-7059-2023, 2023
Short summary
Short summary
We demonstrate how, given a simulation of fluid and rock interacting, we can emulate the system using machine learning. This means that, for a given initial condition, we can predict the final state, avoiding the simulation step once the model has been trained. We present a workflow for applying this approach to any fluid–rock simulation and showcase two applications to different fluid–rock simulations. This approach has applications for improving model development and sensitivity analyses.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-223, https://doi.org/10.5194/gmd-2023-223, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion by either uniform erosion processes where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea level history, material properties, and the relative influence of different erosional processes.
Yaqi Wang, Lanning Wang, Juan Feng, Zhenya Song, Qizhong Wu, and Huaqiong Cheng
Geosci. Model Dev., 16, 6857–6873, https://doi.org/10.5194/gmd-16-6857-2023, https://doi.org/10.5194/gmd-16-6857-2023, 2023
Short summary
Short summary
In this study, to noticeably improve precipitation simulation in steep mountains, we propose a sub-grid parameterization scheme for the topographic vertical motion in CAM5-SE to revise the original vertical velocity by adding the topographic vertical motion. The dynamic lifting effect of topography is extended from the lowest layer to multiple layers, thus improving the positive deviations of precipitation simulation in high-altitude regions and negative deviations in low-altitude regions.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
EGUsphere, https://doi.org/10.5194/egusphere-2023-2720, https://doi.org/10.5194/egusphere-2023-2720, 2023
Short summary
Short summary
We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth System Models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Cited articles
Allen, R., Pereira, L., Raes, D., and Smith, M.: Crop evapotranspiration
Guidelines for computing crop water requirements, FAO Irrigation and
Drainage Paper No. 56, https://www.fao.org/3/x0490e/x0490e00.htm, (last access: January 2023), 1998.
Asfaw, D. T., Singer, M. B., Rosolem, R., MacLeod, D., Cuthbert, M., Miguitama, E. Q., Gaona, M. F. R., and Michaelides, K.: stoPET_v1, figshare [code and data set],
https://doi.org/10.6084/m9.figshare.19665531, 2023.
Ayyad, S. and Khalifa, M.: Will the Eastern Nile countries be able to
sustain their crop production by 2050? An outlook from water and land
perspectives, Sci. Total Environ., 775, 145769,
https://doi.org/10.1016/j.scitotenv.2021.145769, 2021.
Bai, P., Liu, X., Yang, T., Li, F., Liang, K., Hu, S., and Liu, C.:
Assessment of the influences of different potential evapotranspiration
inputs on the performance of monthly hydrological models under different
climatic conditions, J. Hydrometeorol., 17, 2259–2274,
https://doi.org/10.1175/JHM-D-15-0202.1, 2016.
Blunden, J. and Arndt, D. S.: State of the Climate in 2019, B.
Am. Meteorol. Soc., 101, Si–S429,
https://doi.org/10.1175/2020BAMSStateoftheClimate.1, 2020.
Bowman, A. L., Franz, K. J., Hogue, T. S., and Kinoshita, A. M.: MODIS-Based
Potential Evapotranspiration Demand Curves for the Sacramento Soil Moisture
Accounting Model, J. Hydrol. Eng., 21, 04015055,
https://doi.org/10.1061/(asce)he.1943-5584.0001261, 2016.
Chen, J., Brissette, F., and Leconte, R.: WeaGETS a Matlab-based daily scale
weather generator for generating precipitation and temperature, Procedia
Environmental Sciences, 13, 2222–2235, https://doi.org/10.1016/j.proenv.2012.01.211,
2012.
Condon, L. E., Atchley, A. L., and Maxwell, R. M.: Evapotranspiration
depletes groundwater under warming over the contiguous United States, Nat.
Commun., 11, 873, https://doi.org/10.1038/s41467-020-14688-0, 2020.
Dallaire, G., Poulin, A., Arsenault, R., and Brissette, F.: Uncertainty of
potential evapotranspiration modelling in climate change impact studies on
low flows in North America, Hydrolog. Sci. J., 66, 689–702,
https://doi.org/10.1080/02626667.2021.1888955, 2021.
De Luca, D. L., Petroselli, A., and Galasso, L.: A transient stochastic
rainfall generator for climate changes analysis at hydrological scales in
central Italy, Atmosphere, 11, 1–21, https://doi.org/10.3390/atmos11121292, 2020.
Dimitriadis, P., Tegos, A., and Koutsoyiannis, D.: Stochastic analysis of
hourly to monthly potential evapotranspiration with a focus on the
long-range dependence and application with reanalysis and ground-station
data, Hydrology, 8, 177, https://doi.org/10.3390/hydrology8040177, 2021.
Ewaid, S. H. and Abed, S. A.: Crop Water Requirements and Irrigation
Schedules for Some Major Crops in Southern Iraq, MDPI-Water, 11, 756,
https://doi.org/10.3390/w11040756, 2019.
Fatichi, S., Ivanov, V. Y., and Caporali, E.: Simulation of future climate
scenarios with a weather generator, Adv. Water Resour., 34,
448–467, https://doi.org/10.1016/j.advwatres.2010.12.013, 2011.
FEWS NET: Millions Already Face Starvation in Eastern Horn of Africa, Fifth Consecutive Season of Drought Now Forecast, 13 June 2022 press release, https://fews.net (last access: January 2023), 2022a.
FEWS NET: Unprecedented Sixth Consecutive Season of
Drought Forecast in Horn of Africa: Hunger Surges as Humanitarian Efforts Remain Underfunded, 7 November 2022 press release, https://fews.net (last access: January 2023), 2022b.
Funk, C., Dettinger, M. D., Michaelsen, J. C., Verdin, J. P., Brown, M. E.,
Barlow, M., and Hoell, A.: Warming of the Indian Ocean threatens eastern and
southern African food security but could be mitigated by agricultural
development, P. Natl. Acad. Sci. USA, 105, 11081–11086, https://doi.org/10.1073/pnas.0708196105, 2008.
Funk, C. C. and Brown, M. E.: Declining global per capita agricultural
production and warming oceans threaten food security, Food Security, 1,
271–289, https://doi.org/10.1007/s12571-009-0026-y, 2009.
Grismer, M. E., Orang, M., Snyder, R., and Matyac, R.: Pan Evaporation to
Reference Evapotranspiration Conversion Methods, J. Irrig.
Drain. E., 128, 180–184,
https://doi.org/10.1061/(asce)0733-9437(2002)128:3(180), 2002.
Harris, I., Osborn, T. J., Jones, P., and Lister, D.: Version 4 of the CRU TS
monthly high-resolution gridded multivariate
climate dataset, Sci. Data, 7, 1–18,
https://doi.org/10.1038/s41597-020-0453-3, 2020 (data available at: https://crudata.uea.ac.uk/cru/data/hrg/, last access: January 2023).
Helsel, D. R., Hirsch, R. M., Ryberg, K., Archfield, S., and Gilroy, E.:
Statistical Methods in Water Resources Techniques and Methods 4 A3, USGS Techniques and Methods, https://doi.org/10.3133/tm4A3, 2020.
Hoegh-Guldberg, O., Jacob, D., Taylor, M., Bindi, M., Brown, S., Camilloni,
I., Diedhiou, A., Djalante, R., Ebi, K., Engelbrecht, F., Guiot, J.,
Hijioka, Y., Mehrotra, S., Payne, A., Seneviratne, S. I., Thomas, A.,
Warren, R., and Zhou, G.: Impacts of 1.5 ∘C Global Warming on
Natural and Human Systems, in:
Global warming of 1.5 ∘C, An IPCC Special Report on the impacts of global warming of 1.5 ∘C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, edited by: Masson-Delmotte, V., Zhai, P.,
Pörtner, H. O., Roberts, D., Skea, J., Shukla, P. R., Pirani, A., Moufouma-Okia, W.,
Péan, C., Pidcock, R., Connors, S., Matthews, J. B. R., Chen, Y., Zhou, X., Gomis, M.
I., Lonnoy, E., Maycock, T., Tignor, M. and Waterfield, T., Cambridge University Press, Cambridge, UK and New York, NY, USA, 175–312, https://doi.org/10.1017/9781009157940.005, 2018.
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of
Working Group 1 to the 5th Assessment Report of the Intergovernmental Panel
on Climate Change, in: Energy and Environment, edited by: Stocker, T., Qin,
D., Plattner, G.-K., Tignor, M., Allen, S., Boschung, J., Nauels, A., Xia,
Y., Bex, V., and Midgley, P., Cambridge University Press,
Cambridge, United Kingdom and New York, NY, USA,
https://doi.org/10.1260/095830507781076194, 2013.
IPCC: Climate Change 2021: The Physical Science Basis, Contribution of
Working Group I to the Sixth Assessment Report of the Intergovernmental
Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A.
Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I.,
Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K.,
Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2391 pp., https://doi.org/10.1017/9781009157896, 2021.
Kang, Y., Khan, S., and Ma, X.: Climate change impacts on crop yield, crop
water productivity and food security – A review, Prog. Nat.
Sci., 19, 1665–1674, https://doi.org/10.1016/j.pnsc.2009.08.001, 2009.
King, L. M., Mcleod, A. I., and Simonovic, S. P.: Improved Weather Generator
Algorithm for Multisite Simulation of Precipitation and Temperature, J.
Am. Water Resour. Assoc., 51, 1305–1320,
https://doi.org/10.1111/1752-1688.12307, 2015.
Kingston, D. G., Todd, M. C., Taylor, R. G., Thompson, J. R., and Arnell,
N. W.: Uncertainty in the estimation of potential evapotranspiration under
climate change, Geophys. Res. Lett., 36, 3–8,
https://doi.org/10.1029/2009GL040267, 2009.
Kriegler, E., Bertram, C., Kuramochi, T., Jakob, M., Pehl, M.,
Stevanovıc, M., Höhne, N., Luderer, G.,
Minx, J. C., Fekete, H., Hilaire, J., Luna, L., Popp, A., Steckel, J. C.,
Sterl, S., Yalew, A. W., Dietrich, J. P., and Edenhofer, O.: Short term
policies to keep the door open for Paris climate goals, Environ.
Res. Lett., 13, 7, https://doi.org/10.1088/1748-9326/aac4f1, 2018.
Lee, K.-H. and Cho, H.-Y.: Simple Method for Estimating Pan Coefficients:
Conversion of Pan Evaporation to Reference Evapotranspiration, J.
Irrig. Drain. E., 138, 98–103,
https://doi.org/10.1061/(asce)ir.1943-4774.0000379, 2012.
Li, S., Kang, S., Zhang, L., Zhang, J., Du, T., Tong, L., and Ding, R.:
Evaluation of six potential evapotranspiration models for estimating crop
potential and actual evapotranspiration in arid regions, J.
Hydrol., 543, 450–461, https://doi.org/10.1016/j.jhydrol.2016.10.022, 2016.
Liu, Z., Yao, Z., and Wang, R.: Simulation and evaluation of actual
evapotranspiration based on inverse hydrological modeling at a basin scale,
Catena, 180, 160–168, https://doi.org/10.1016/j.catena.2019.03.039, 2019.
Maxwell, R. M. and Miller, N. L.: On the development of a coupled land
surface and groundwater model, Dev. Water Sci., 55,
1503–1510, https://doi.org/10.1016/S0167-5648(04)80161-8, 2005.
Mayes, M., Caylor, K. K., Singer, M. B., Stella, J. C., Roberts, D., and
Nagler, P.: Climate sensitivity of water use by riparian woodlands at
landscape scales, Hydrol. Process., 34, 4884–4903,
https://doi.org/10.1002/hyp.13942, 2020.
Mohawesh, O. E.: Evaluation of evapotranspiration models for estimating
daily reference evapotranspiration in arid and semiarid environments, Plant
Soil Environ., 57, 145–152, https://doi.org/10.17221/240/2010-pse, 2011.
Muñoz Sabater, J.: ERA5-Land hourly data from 1981 to present,
Copernicus Climate Change Service (C3S) Climate Data
Store (CDS) [data set],
https://doi.org/10.24381/cds.e2161bac, 2019.
NOAA: NOAA National Centers for Environmental Information, State of the
Climate: Global Climate Report for Annual 2020,
https://www.ncdc.noaa.gov/sotc/global/202013 (last access: 31 March 2022), 2021.
Nyakudya, I. W. and Stroosnijder, L.: Water management options based on
rainfall analysis for rainfed maize (Zea mays L.) production in Rushinga
district, Zimbabwe, Agr. Water Manage., 98, 1649–1659,
https://doi.org/10.1016/j.agwat.2011.06.002, 2011.
Peleg, N., Fatichi, S., Paschalis, A., Molnar, P., and Burlando, P.: An
advanced stochastic weather generator for simulating 2-D high-resolution
climate variables, J. Adv. Model. Earth Sy.,
9, 1595–1627, https://doi.org/10.1002/2016MS000854, 2017.
Quichimbo, E. A., Singer, M. B., Michaelides, K., Hobley, D. E. J., Rosolem, R., and Cuthbert, M. O.: DRYP 1.0: a parsimonious hydrological model of DRYland Partitioning of the water balance, Geosci. Model Dev., 14, 6893–6917, https://doi.org/10.5194/gmd-14-6893-2021, 2021.
Randalls, S.: History of the 2C climate target, Wires. Clim. Change, 1, 598–605, https://doi.org/10.1002/wcc.62, 2010.
Ravazzani, G., Corbari, C., Morella, S., Gianoli, P., and Mancini, M.:
Modified Hargreaves-Samani Equation for the Assessment of Reference
Evapotranspiration in Alpine River Basins, J. Irrig.
Drain. E, 138, 592–599, https://doi.org/10.1061/(asce)ir.1943-4774.0000453,
2012.
Raziei, T. and Pereira, L. S.: Estimation of ETo with Hargreaves-Samani and
FAO-PM temperature methods for a wide range of climates in Iran,
Agr. Water Manage., 121, 1–18,
https://doi.org/10.1016/j.agwat.2012.12.019, 2013.
Sabathier, R., Singer, M. B., Stella, J. C., Roberts, D. A., and Caylor, K.
K.: Vegetation responses to climatic and geologic controls on water
availability in southeastern Arizona, Environ. Res. Lett., 16, 6,
https://doi.org/10.1088/1748-9326/abfe8c, 2021.
Singer, M., Asfaw, A., Rosolem, R., Cuthbert, M. O., Miralles, D. G., Miguitama, E. Q., MacLeod, D., and Michaelides, K.:
Hourly potential evapotranspiration (hPET) at 0.1degs grid resolution for the global land surface from 1981-present, University of Bristol [data set], https://doi.org/10.5523/bris.qb8ujazzda0s2aykkv0oq0ctp, 2020.
Singer, M. B., Michaelides, K., and Hobley, D. E. J.: STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change, Geosci. Model Dev., 11, 3713–3726, https://doi.org/10.5194/gmd-11-3713-2018, 2018.
Singer, M. B., Asfaw, D. T., Rosolem, R., Cuthbert, M. O., Miralles, D. G.,
MacLeod, D., Quichimbo, E. A., and Michaelides, K.: Hourly potential
evapotranspiration at 0.1 resolution for the global land surface from
1981-present, Sci. Data, 8, 1–13, https://doi.org/10.1038/s41597-021-01003-9,
2021.
Steinschneider, S., Ray, P., Rahat, S. H., and Kucharski, J.: A
Weather-Regime-Based Stochastic Weather Generator for Climate Vulnerability
Assessments of Water Systems in the Western United States, Water Resour.
Res., 55, 6923–6945, https://doi.org/10.1029/2018WR024446, 2019.
Tasumi, M.: Estimating evapotranspiration using METRIC model and Landsat
data for better understandings of regional hydrology in the western Urmia
Lake Basin, Agr. Water Manage., 226, 105805,
https://doi.org/10.1016/j.agwat.2019.105805, 2019.
Trabucco, A. and Zomer, R.: Global Aridity Index and Potential
Evapotranspiration (ET0) Climate Database v2.CGIAR Consortium for Spatial
Information (CGIAR-CSI), CGIARCSI
GeoPortal, p. 10,
https://doi.org/10.6084/m9.figshare.7504448.v3, 2018.
Tukimat, N. N. A., Harun, S., and Shahid, S.: Comparison of different
methods in estimating potential evapotranspiration at Muda
Irrigation Scheme of Malaysia, J. Agr. Rural Dev.
Trop., 113, 77–85,
2012.
Valipour, M.: Analysis of potential evapotranspiration using limited weather
data, Appl. Water Sci., 7, 187–197, https://doi.org/10.1007/s13201-014-0234-2,
2017a.
Valipour, M., Gholami Sefidkouhi, M. A., and RaeiniSarjaz, M.: Selecting the
best model to estimate potential evapotranspiration with respect to climate
change and magnitudes of extreme events, Agr. Water Manage., 180,
50–60, https://doi.org/10.1016/j.agwat.2016.08.025, 2017b.
van Osnabrugge, B., Uijlenhoet, R., and Weerts, A.: Contribution of potential evaporation forecasts to 10-day streamflow forecast skill for the Rhine River, Hydrol. Earth Syst. Sci., 23, 1453–1467, https://doi.org/10.5194/hess-23-1453-2019, 2019.
Warter, M. M., Singer, M. B., Cuthbert, M. O., Roberts, D., Caylor, K. K., Sabathier, R., and Stella, J.: Drought onset and propagation into soil moisture and grassland vegetation responses during the 2012–2019 major drought in Southern California, Hydrol. Earth Syst. Sci., 25, 3713–3729, https://doi.org/10.5194/hess-25-3713-2021, 2021.
Will, A., Akhtar, N., Brauch, J., Breil, M., Davin, E., Ho-Hagemann, H. T. M., Maisonnave, E., Thürkow, M., and Weiher, S.: The COSMO-CLM 4.8 regional climate model coupled to regional ocean, land surface and global earth system models using OASIS3-MCT: description and performance, Geosci. Model Dev., 10, 1549–1586, https://doi.org/10.5194/gmd-10-1549-2017, 2017.
Xu, Y.-P., Pan, S., Fu, G., Tian, Y., and Zhang, X.: Future potential
evapotranspiration changes and contribution analysis in Zhejiang Province,
East China, J. Geophys. Res., 19, 456–476,
https://doi.org/10.1002/2014JD021891, 2014.
Yadeta, D., Kebede, A., and Tessema, N.: Potential evapotranspiration models
evaluation, modelling, and projection under climate scenarios, Kesem
sub-basin, Awash River basin, Ethiopia, Modeling Earth Systems and
Environment, 6, 2165–2176, https://doi.org/10.1007/s40808-020-00831-9, 2020.
Zhou, J., Wang, Y., Su, B., Wang, A., Tao, H., Zhai, J., Kundzewicz, Z. W.,
and Jiang, T.: Choice of potential evapotranspiration formulas influences
drought assessment: A case study in China, Atmos. Res., 242, 104979, https://doi.org/10.1016/j.atmosres.2020.104979, 2020.
Zoccatelli, D., Marra, F., Armon, M., Rinat, Y., Smith, J. A., and Morin, E.: Contrasting rainfall-runoff characteristics of floods in desert and Mediterranean basins, Hydrol. Earth Syst. Sci., 23, 2665–2678, https://doi.org/10.5194/hess-23-2665-2019, 2019.
Short summary
stoPET is a new stochastic potential evapotranspiration (PET) generator for the globe at hourly resolution. Many stochastic weather generators are used to generate stochastic rainfall time series; however, no such model exists for stochastically generating plausible PET time series. As such, stoPET represents a significant methodological advance. stoPET generate many realizations of PET to conduct climate studies related to the water balance, agriculture, water resources, and ecology.
stoPET is a new stochastic potential evapotranspiration (PET) generator for the globe at hourly...
