Articles | Volume 15, issue 10
https://doi.org/10.5194/gmd-15-4193-2022
© Author(s) 2022. 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-15-4193-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at kilometre scale
Juan Manuel Castillo
CORRESPONDING AUTHOR
Met Office, Exeter, EX1 3PB, UK
Huw W. Lewis
Met Office, Exeter, EX1 3PB, UK
Akhilesh Mishra
National Centre for Medium Range Weather Forecasting (NCMRWF), Noida, India
Ashis Mitra
National Centre for Medium Range Weather Forecasting (NCMRWF), Noida, India
Jeff Polton
National Oceanography Centre, Liverpool, UK
Ashley Brereton
National Oceanography Centre, Liverpool, UK
Andrew Saulter
Met Office, Exeter, EX1 3PB, UK
Alex Arnold
Met Office, Exeter, EX1 3PB, UK
Segolene Berthou
Met Office, Exeter, EX1 3PB, UK
Douglas Clark
UK Centre of Ecology & Hydrology (UKCEH), Wallingford, UK
Julia Crook
School of Earth and Environment, University of Leeds, Leeds, UK
Ananda Das
India Meteorological Department (IMD), Delhi, India
John Edwards
Met Office, Exeter, EX1 3PB, UK
Xiangbo Feng
Department of Meteorology, University of Reading, Reading, UK
Ankur Gupta
National Centre for Medium Range Weather Forecasting (NCMRWF), Noida, India
Sudheer Joseph
Indian National Centre for Ocean Information Services (INCOIS), Hyderabad, India
Nicholas Klingaman
Department of Meteorology, University of Reading, Reading, UK
Imranali Momin
National Centre for Medium Range Weather Forecasting (NCMRWF), Noida, India
Christine Pequignet
Met Office, Exeter, EX1 3PB, UK
Claudio Sanchez
Met Office, Exeter, EX1 3PB, UK
Jennifer Saxby
School of Earth and Environment, University of Leeds, Leeds, UK
Maria Valdivieso da Costa
Department of Meteorology, University of Reading, Reading, UK
Related authors
Jennifer Saxby, Julia Crook, Simon Peatman, Cathryn Birch, Juliane Schwendike, Maria Valdivieso da Costa, Juan Manuel Castillo Sanchez, Chris Holloway, Nicholas P. Klingaman, Ashis Mitra, and Huw Lewis
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2021-46, https://doi.org/10.5194/wcd-2021-46, 2021
Preprint withdrawn
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This study assesses the ability of the new Met Office IND1 numerical model to simulate tropical cyclones and their associated hazards, such as high winds and heavy rainfall. The new system consists of both atmospheric and oceanic models coupled together, allowing us to explore the sensitivity of cyclones to important air–sea feedbacks. We find that the model can accurately simulate tropical cyclone position, structure, and intensity, which are crucial for predicting and mitigating hazards.
Huw W. Lewis, John Siddorn, Juan Manuel Castillo Sanchez, Jon Petch, John M. Edwards, and Tim Smyth
Ocean Sci., 15, 761–778, https://doi.org/10.5194/os-15-761-2019, https://doi.org/10.5194/os-15-761-2019, 2019
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Oceans are modified at the surface by winds and by the exchange of heat with the atmosphere. The effect of changing atmospheric information that is available to drive an ocean model of north-west Europe, which can simulate small-scale details of the ocean state, is tested. We show that simulated temperatures agree better with observations located near the coast around the south-west UK when using data from a high-resolution atmospheric model, and when atmosphere and ocean feedbacks are included.
Huw W. Lewis, Juan Manuel Castillo Sanchez, Alex Arnold, Joachim Fallmann, Andrew Saulter, Jennifer Graham, Mike Bush, John Siddorn, Tamzin Palmer, Adrian Lock, John Edwards, Lucy Bricheno, Alberto Martínez-de la Torre, and James Clark
Geosci. Model Dev., 12, 2357–2400, https://doi.org/10.5194/gmd-12-2357-2019, https://doi.org/10.5194/gmd-12-2357-2019, 2019
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In the real world the atmosphere, oceans and land surface are closely interconnected, and yet the prediction systems used for weather and ocean forecasting tend to treat them in isolation. This paper describes the third version of a regional modelling system which aims to represent the feedback processes between sky, sea and land. The main innovation introduced in this version enables waves to affect the underlying ocean. Coupled results from four different month-long simulations are analysed.
Huw W. Lewis, Juan Manuel Castillo Sanchez, John Siddorn, Robert R. King, Marina Tonani, Andrew Saulter, Peter Sykes, Anne-Christine Pequignet, Graham P. Weedon, Tamzin Palmer, Joanna Staneva, and Lucy Bricheno
Ocean Sci., 15, 669–690, https://doi.org/10.5194/os-15-669-2019, https://doi.org/10.5194/os-15-669-2019, 2019
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Forecasts of ocean temperature, salinity, currents, and sea height can be improved by linking state-of-the-art ocean and wave models, so that they can interact to better represent the real world. We test this approach in an ocean model of north-west Europe which can simulate small-scale details of the ocean state. The intention is to implement the system described in this study for operational use so that improved information can be provided to users of ocean forecast data.
Jennifer A. Graham, Enda O'Dea, Jason Holt, Jeff Polton, Helene T. Hewitt, Rachel Furner, Karen Guihou, Ashley Brereton, Alex Arnold, Sarah Wakelin, Juan Manuel Castillo Sanchez, and C. Gabriela Mayorga Adame
Geosci. Model Dev., 11, 681–696, https://doi.org/10.5194/gmd-11-681-2018, https://doi.org/10.5194/gmd-11-681-2018, 2018
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This paper describes the next-generation ocean forecast model for the European NW shelf, AMM15 (Atlantic Margin Model, 1.5 km resolution). The current forecast system has a resolution of 7 km. While this is sufficient to represent large-scale circulation, many dynamical features (such as eddies, frontal jets, and internal tides) can only begin to be resolved at 0–1 km resolution. Here we introduce AMM15 and demonstrate its ability to represent the mean state and variability of the region.
Huw W. Lewis, Juan Manuel Castillo Sanchez, Jennifer Graham, Andrew Saulter, Jorge Bornemann, Alex Arnold, Joachim Fallmann, Chris Harris, David Pearson, Steven Ramsdale, Alberto Martínez-de la Torre, Lucy Bricheno, Eleanor Blyth, Victoria A. Bell, Helen Davies, Toby R. Marthews, Clare O'Neill, Heather Rumbold, Enda O'Dea, Ashley Brereton, Karen Guihou, Adrian Hines, Momme Butenschon, Simon J. Dadson, Tamzin Palmer, Jason Holt, Nick Reynard, Martin Best, John Edwards, and John Siddorn
Geosci. Model Dev., 11, 1–42, https://doi.org/10.5194/gmd-11-1-2018, https://doi.org/10.5194/gmd-11-1-2018, 2018
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In the real world the atmosphere, oceans and land surface are closely interconnected, and yet prediction systems tend to treat them in isolation. Those feedbacks are often illustrated in natural hazards, such as when strong winds lead to large waves and coastal damage, or when prolonged rainfall leads to saturated ground and high flowing rivers. For the first time, we have attempted to represent some of the feedbacks between sky, sea and land within a high-resolution forecast system for the UK.
Kunal Madkaiker, Ambarukhana D. Rao, and Sudheer Joseph
EGUsphere, https://doi.org/10.5194/egusphere-2023-3011, https://doi.org/10.5194/egusphere-2023-3011, 2024
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Based on a validated high-resolution model, we estimated the volume, freshwater and heat transports along Indian coasts. Influenced by coastal currents, transport along eastern coast is highly seasonal and western coast is impacted by intraseasonal oscillations. Alongshore and cross-shore transports show inverse relationship on western coast and are in phase on eastern coast. The North Indian Ocean functions as a heat source or sink depending on the seasonal flow of meridional heat transport.
Claudio Sanchez, Suzanne Gray, Ambrogio Volonte, Florian Pantillon, Segolene Berthou, and Silvio Davolio
EGUsphere, https://doi.org/10.5194/egusphere-2023-2431, https://doi.org/10.5194/egusphere-2023-2431, 2023
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Medicane Ianos was a very intense cyclone which led to harmful impacts over Greece. We explore what processes are important for the forecasting of medicane Ianos, with the use of the MetOffice weather model. There is a preceding precipitation event before Ianos’s birth, whose energetics generate a bubble in the tropopause. This bubble creates the necessary conditions for Ianos to emerge and strengthen, the processes are enhanced in simulations with a warmer Mediterranean Sea.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
Emma Howard, Steven Woolnough, Nicolas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-165, https://doi.org/10.5194/gmd-2023-165, 2023
Revised manuscript accepted for GMD
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This paper describes a coupled atmosphere-mixed layer ocean simulation setup that will be used to study weather processes in South East Asia. The set up has been used to compare high resolution simulations, which are able to partially represent storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
David Byrne, Jeff Polton, Enda O'Dea, and Joanne Williams
Geosci. Model Dev., 16, 3749–3764, https://doi.org/10.5194/gmd-16-3749-2023, https://doi.org/10.5194/gmd-16-3749-2023, 2023
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Validation is a crucial step during the development of models for ocean simulation. The purpose of validation is to assess how accurate a model is. It is most commonly done by comparing output from a model to actual observations. In this paper, we introduce and demonstrate usage of the COAsT Python package to standardise the validation process for physical ocean models. We also discuss our five guiding principles for standardised validation.
Christian Ferrarin, Florian Pantillon, Silvio Davolio, Marco Bajo, Mario Marcello Miglietta, Elenio Avolio, Diego S. Carrió, Ioannis Pytharoulis, Claudio Sanchez, Platon Patlakas, Juan Jesús González-Alemán, and Emmanouil Flaounas
Nat. Hazards Earth Syst. Sci., 23, 2273–2287, https://doi.org/10.5194/nhess-23-2273-2023, https://doi.org/10.5194/nhess-23-2273-2023, 2023
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The combined use of meteorological and ocean models enabled the analysis of extreme sea conditions driven by Medicane Ianos, which hit the western coast of Greece on 18 September 2020, flooding and damaging the coast. The large spread associated with the ensemble highlighted the high model uncertainty in simulating such an extreme weather event. The different simulations have been used for outlining hazard scenarios that represent a fundamental component of the coastal risk assessment.
Nieves G. Valiente, Andrew Saulter, Breogan Gomez, Christopher Bunney, Jian-Guo Li, Tamzin Palmer, and Christine Pequignet
Geosci. Model Dev., 16, 2515–2538, https://doi.org/10.5194/gmd-16-2515-2023, https://doi.org/10.5194/gmd-16-2515-2023, 2023
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We document the Met Office operational global and regional wave models which provide wave forecasts up to 7 d ahead. Our models present coarser resolution offshore to higher resolution near the coastline. The increased resolution led to replication of the extremes but to some overestimation during modal conditions. If currents are included, wave directions and long period swells near the coast are significantly improved. New developments focus on the optimisation of the models with resolution.
Mike Bush, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Aravindakshan Jayakumar, Huw Lewis, Adrian Lock, Marion Mittermaier, Saji Mohandas, Rachel North, Aurore Porson, Belinda Roux, Stuart Webster, and Mark Weeks
Geosci. Model Dev., 16, 1713–1734, https://doi.org/10.5194/gmd-16-1713-2023, https://doi.org/10.5194/gmd-16-1713-2023, 2023
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Building on the baseline of RAL1, the RAL2 science configuration is used for regional modelling around the UM partnership and in operations at the Met Office. RAL2 has been tested in different parts of the world including Australia, India and the UK. RAL2 increases medium and low cloud amounts in the mid-latitudes compared to RAL1, leading to improved cloud forecasts and a reduced diurnal cycle of screen temperature. There is also a reduction in the frequency of heavier precipitation rates.
Julia Crook, Cornelia Klein, Sonja Folwell, Christopher M. Taylor, Douglas J. Parker, Adama Bamba, and Kouakou Kouadio
Weather Clim. Dynam., 4, 229–248, https://doi.org/10.5194/wcd-4-229-2023, https://doi.org/10.5194/wcd-4-229-2023, 2023
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We estimate recent deforestation in West Africa and use a climate model allowing explicit convection to determine impacts on early season rainfall. We find enhanced rainfall over deforestation, in line with recent observational results, due to changes in circulation rather than humidity, showing potential for future studies. Local changes depend on initial soil moisture, deforestation extent, and ocean proximity, with sea breezes shifting inland where surface friction decreased.
Jeff Polton, James Harle, Jason Holt, Anna Katavouta, Dale Partridge, Jenny Jardine, Sarah Wakelin, Julia Rulent, Anthony Wise, Katherine Hutchinson, David Byrne, Diego Bruciaferri, Enda O'Dea, Michela De Dominicis, Pierre Mathiot, Andrew Coward, Andrew Yool, Julien Palmiéri, Gennadi Lessin, Claudia Gabriela Mayorga-Adame, Valérie Le Guennec, Alex Arnold, and Clément Rousset
Geosci. Model Dev., 16, 1481–1510, https://doi.org/10.5194/gmd-16-1481-2023, https://doi.org/10.5194/gmd-16-1481-2023, 2023
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The aim is to increase the capacity of the modelling community to respond to societally important questions that require ocean modelling. The concept of reproducibility for regional ocean modelling is developed: advocating methods for reproducible workflows and standardised methods of assessment. Then, targeting the NEMO framework, we give practical advice and worked examples, highlighting key considerations that will the expedite development cycle and upskill the user community.
Thibault Hallouin, Richard J. Ellis, Douglas B. Clark, Simon J. Dadson, Andrew G. Hughes, Bryan N. Lawrence, Grenville M. S. Lister, and Jan Polcher
Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, https://doi.org/10.5194/gmd-15-9177-2022, 2022
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A new framework for modelling the water cycle in the land system has been implemented. It considers the hydrological cycle as three interconnected components, bringing flexibility in the choice of the physical processes and their spatio-temporal resolutions. It is designed to foster collaborations between land surface, hydrological, and groundwater modelling communities to develop the next-generation of land system models for integration in Earth system models.
Diego Bruciaferri, Marina Tonani, Isabella Ascione, Fahad Al Senafi, Enda O'Dea, Helene T. Hewitt, and Andrew Saulter
Geosci. Model Dev., 15, 8705–8730, https://doi.org/10.5194/gmd-15-8705-2022, https://doi.org/10.5194/gmd-15-8705-2022, 2022
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More accurate predictions of the Gulf's ocean dynamics are needed. We investigate the impact on the predictive skills of a numerical shelf sea model of the Gulf after changing a few key aspects. Increasing the lateral and vertical resolution and optimising the vertical coordinate system to best represent the leading physical processes at stake significantly improve the accuracy of the simulated dynamics. Additional work may be needed to get real benefit from using a more realistic bathymetry.
Rebecca J. Oliver, Lina M. Mercado, Doug B. Clark, Chris Huntingford, Christopher M. Taylor, Pier Luigi Vidale, Patrick C. McGuire, Markus Todt, Sonja Folwell, Valiyaveetil Shamsudheen Semeena, and Belinda E. Medlyn
Geosci. Model Dev., 15, 5567–5592, https://doi.org/10.5194/gmd-15-5567-2022, https://doi.org/10.5194/gmd-15-5567-2022, 2022
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We introduce new representations of plant physiological processes into a land surface model. Including new biological understanding improves modelled carbon and water fluxes for the present in tropical and northern-latitude forests. Future climate simulations demonstrate the sensitivity of photosynthesis to temperature is important for modelling carbon cycle dynamics in a warming world. Accurate representation of these processes in models is necessary for robust predictions of climate change.
Mahdi André Nakhavali, Lina M. Mercado, Iain P. Hartley, Stephen Sitch, Fernanda V. Cunha, Raffaello di Ponzio, Laynara F. Lugli, Carlos A. Quesada, Kelly M. Andersen, Sarah E. Chadburn, Andy J. Wiltshire, Douglas B. Clark, Gyovanni Ribeiro, Lara Siebert, Anna C. M. Moraes, Jéssica Schmeisk Rosa, Rafael Assis, and José L. Camargo
Geosci. Model Dev., 15, 5241–5269, https://doi.org/10.5194/gmd-15-5241-2022, https://doi.org/10.5194/gmd-15-5241-2022, 2022
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In tropical ecosystems, the availability of rock-derived elements such as P can be very low. Thus, without a representation of P cycling, tropical forest responses to rising atmospheric CO2 conditions in areas such as Amazonia remain highly uncertain. We introduced P dynamics and its interactions with the N and P cycles into the JULES model. Our results highlight the potential for high P limitation and therefore lower CO2 fertilization capacity in the Amazon forest with low-fertility soils.
Toby R. Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry D. Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci., 26, 3151–3175, https://doi.org/10.5194/hess-26-3151-2022, https://doi.org/10.5194/hess-26-3151-2022, 2022
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Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and non-random biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
Patrick Le Moigne, Eric Bazile, Anning Cheng, Emanuel Dutra, John M. Edwards, William Maurel, Irina Sandu, Olivier Traullé, Etienne Vignon, Ayrton Zadra, and Weizhong Zheng
The Cryosphere, 16, 2183–2202, https://doi.org/10.5194/tc-16-2183-2022, https://doi.org/10.5194/tc-16-2183-2022, 2022
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This paper describes an intercomparison of snow models, of varying complexity, used for numerical weather prediction or academic research. The results show that the simplest models are, under certain conditions, able to reproduce the surface temperature just as well as the most complex models. Moreover, the diversity of surface parameters of the models has a strong impact on the temporal variability of the components of the simulated surface energy balance.
Ambrogio Volonté, Andrew G. Turner, Reinhard Schiemann, Pier Luigi Vidale, and Nicholas P. Klingaman
Weather Clim. Dynam., 3, 575–599, https://doi.org/10.5194/wcd-3-575-2022, https://doi.org/10.5194/wcd-3-575-2022, 2022
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In this study we analyse the complex seasonal evolution of the East Asian summer monsoon. Using reanalysis data, we show the importance of the interaction between tropical and extratropical air masses converging at the monsoon front, particularly during its northward progression. The upper-level flow pattern (e.g. the westerly jet) controls the balance between the airstreams and thus the associated rainfall. This framework provides a basis for studies of extreme events and climate variability.
Julia Rulent, Lucy M. Bricheno, J. A. Mattias Green, Ivan D. Haigh, and Huw Lewis
Nat. Hazards Earth Syst. Sci., 21, 3339–3351, https://doi.org/10.5194/nhess-21-3339-2021, https://doi.org/10.5194/nhess-21-3339-2021, 2021
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High coastal total water levels (TWLs) can lead to flooding and hazardous conditions for coastal communities and environment. In this research we are using numerical models to study the interactions between the three main components of the TWL (waves, tides, and surges) on UK and Irish coasts during winter 2013/14. The main finding of this research is that extreme waves and surges can indeed happen together, even at high tide, but they often occurred simultaneously 2–3 h before high tide.
Marion Mittermaier, Rachel North, Jan Maksymczuk, Christine Pequignet, and David Ford
Ocean Sci., 17, 1527–1543, https://doi.org/10.5194/os-17-1527-2021, https://doi.org/10.5194/os-17-1527-2021, 2021
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Regions of enhanced chlorophyll-a concentrations can be identified by applying a threshold to the concentration value to a forecast and observed field (or analysis). These regions can then be treated and analysed as features using diagnostic techniques to consider of the evolution of the chlorophyll-a blooms in space and time. This allows us to understand whether the biogeochemistry in the model has any skill in predicting these blooms, their location, intensity, onset, duration and demise.
Jennifer Saxby, Julia Crook, Simon Peatman, Cathryn Birch, Juliane Schwendike, Maria Valdivieso da Costa, Juan Manuel Castillo Sanchez, Chris Holloway, Nicholas P. Klingaman, Ashis Mitra, and Huw Lewis
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2021-46, https://doi.org/10.5194/wcd-2021-46, 2021
Preprint withdrawn
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This study assesses the ability of the new Met Office IND1 numerical model to simulate tropical cyclones and their associated hazards, such as high winds and heavy rainfall. The new system consists of both atmospheric and oceanic models coupled together, allowing us to explore the sensitivity of cyclones to important air–sea feedbacks. We find that the model can accurately simulate tropical cyclone position, structure, and intensity, which are crucial for predicting and mitigating hazards.
Bijoy Thompson, Claudio Sanchez, Boon Chong Peter Heng, Rajesh Kumar, Jianyu Liu, Xiang-Yu Huang, and Pavel Tkalich
Geosci. Model Dev., 14, 1081–1100, https://doi.org/10.5194/gmd-14-1081-2021, https://doi.org/10.5194/gmd-14-1081-2021, 2021
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This article describes the development and ocean forecast evaluation of an atmosphere–ocean coupled prediction system for the Maritime Continent domain, which includes the eastern Indian and western Pacific oceans. The coupled system comprises regional configurations of the atmospheric model MetUM and ocean model NEMO, coupled using the OASIS3-MCT libraries. The model forecast deviation of selected fields relative to observations is within acceptable error limits of operational forecast models.
Simon J. Dadson, Eleanor Blyth, Douglas Clark, Helen Davies, Richard Ellis, Huw Lewis, Toby Marthews, and Ponnambalan Rameshwaran
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-60, https://doi.org/10.5194/hess-2021-60, 2021
Manuscript not accepted for further review
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Flood prediction helps national and regional planning and real-time flood response. In this study we apply and test a new way to make wide area predictions of flooding which can be combined with weather forecasting and climate models to give faster predictions of flooded areas. By simplifying the detailed floodplain topography we can keep track of the fraction of land flooded for hazard mapping purposes. When tested this approach accurately reproduces benchmark datasets for England.
Marie-Estelle Demory, Ségolène Berthou, Jesús Fernández, Silje L. Sørland, Roman Brogli, Malcolm J. Roberts, Urs Beyerle, Jon Seddon, Rein Haarsma, Christoph Schär, Erasmo Buonomo, Ole B. Christensen, James M. Ciarlo ̀, Rowan Fealy, Grigory Nikulin, Daniele Peano, Dian Putrasahan, Christopher D. Roberts, Retish Senan, Christian Steger, Claas Teichmann, and Robert Vautard
Geosci. Model Dev., 13, 5485–5506, https://doi.org/10.5194/gmd-13-5485-2020, https://doi.org/10.5194/gmd-13-5485-2020, 2020
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Now that global climate models (GCMs) can run at similar resolutions to regional climate models (RCMs), one may wonder whether GCMs and RCMs provide similar regional climate information. We perform an evaluation for daily precipitation distribution in PRIMAVERA GCMs (25–50 km resolution) and CORDEX RCMs (12–50 km resolution) over Europe. We show that PRIMAVERA and CORDEX simulate similar distributions. Considering both datasets at such a resolution results in large benefits for impact studies.
Paul-Arthur Monerie, Amulya Chevuturi, Peter Cook, Nicholas P. Klingaman, and Christopher E. Holloway
Geosci. Model Dev., 13, 4749–4771, https://doi.org/10.5194/gmd-13-4749-2020, https://doi.org/10.5194/gmd-13-4749-2020, 2020
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In this study, we assess how increasing the horizontal resolution of HadGEM3-GC31 can allow simulating better tropical and subtropical South American precipitation. We compare simulations of HadGEM3-GC3.1, performed at three different horizontal resolutions. We show that increasing resolution allows decreasing precipitation biases over the Andes and northeast Brazil and improves the simulation of daily precipitation distribution.
Ric Crocker, Jan Maksymczuk, Marion Mittermaier, Marina Tonani, and Christine Pequignet
Ocean Sci., 16, 831–845, https://doi.org/10.5194/os-16-831-2020, https://doi.org/10.5194/os-16-831-2020, 2020
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We assessed the potential benefit of a new verification metric, developed by the atmospheric community, to assess high-resolution ocean models against coarser-resolution configurations. Typical verification metrics often do not show any benefit when high-resolution models are compared to lower-resolution configurations. The new metric showed improvements in higher-resolution models away from the grid scale. The technique can be applied to both deterministic and ensemble forecasts.
Mike Bush, Tom Allen, Caroline Bain, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Humphrey Lean, Adrian Lock, James Manners, Marion Mittermaier, Cyril Morcrette, Rachel North, Jon Petch, Chris Short, Simon Vosper, David Walters, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Nigel Wood, and Mohamed Zerroukat
Geosci. Model Dev., 13, 1999–2029, https://doi.org/10.5194/gmd-13-1999-2020, https://doi.org/10.5194/gmd-13-1999-2020, 2020
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In this paper we define the first Regional Atmosphere and Land (RAL) science configuration for kilometre-scale modelling using the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL1 defines the science configuration of the dynamics and physics schemes of the atmosphere and land. This configuration will provide a model baseline for any future weather or climate model developments to be described against.
Emma L. Robinson and Douglas B. Clark
Hydrol. Earth Syst. Sci., 24, 1763–1779, https://doi.org/10.5194/hess-24-1763-2020, https://doi.org/10.5194/hess-24-1763-2020, 2020
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This study used a water balance approach based on GRACE total water storage to infer the amount of cold-season precipitation in four Arctic river basins. This was used to evaluate four gridded meteorological data sets, which were used as inputs to a land surface model. We found that the cold-season precipitation in these data sets needed to be increased by up to 55 %. Using these higher precipitation inputs improved the model representation of Arctic hydrology, particularly lying snow.
Andrew J. Wiltshire, Maria Carolina Duran Rojas, John M. Edwards, Nicola Gedney, Anna B. Harper, Andrew J. Hartley, Margaret A. Hendry, Eddy Robertson, and Kerry Smout-Day
Geosci. Model Dev., 13, 483–505, https://doi.org/10.5194/gmd-13-483-2020, https://doi.org/10.5194/gmd-13-483-2020, 2020
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We present the Global Land (GL) configuration of the Joint UK Land Environment Simulator (JULES). JULES-GL7 can be used to simulate the exchange of heat, water and momentum over land and is therefore applicable for helping understand past and future changes, and forms the land component of the HadGEM3-GC3.1 climate model. The configuration is freely available subject to licence restrictions.
Marina Tonani, Peter Sykes, Robert R. King, Niall McConnell, Anne-Christine Péquignet, Enda O'Dea, Jennifer A. Graham, Jeff Polton, and John Siddorn
Ocean Sci., 15, 1133–1158, https://doi.org/10.5194/os-15-1133-2019, https://doi.org/10.5194/os-15-1133-2019, 2019
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A new high-resolution ocean model at 1.5 km has replaced the 7 km system for delivering short-term forecasts of the North-West European Shelf seas. The products (temperature, salinity, currents, and sea surface height) are available on the Copernicus Marine Service catalogue. This study focuses on the high-resolution impact on the quality of the products delivered to the users. Results show that the high-resolution model is better at resolving the variability of the physical variables.
Huw W. Lewis, John Siddorn, Juan Manuel Castillo Sanchez, Jon Petch, John M. Edwards, and Tim Smyth
Ocean Sci., 15, 761–778, https://doi.org/10.5194/os-15-761-2019, https://doi.org/10.5194/os-15-761-2019, 2019
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Oceans are modified at the surface by winds and by the exchange of heat with the atmosphere. The effect of changing atmospheric information that is available to drive an ocean model of north-west Europe, which can simulate small-scale details of the ocean state, is tested. We show that simulated temperatures agree better with observations located near the coast around the south-west UK when using data from a high-resolution atmospheric model, and when atmosphere and ocean feedbacks are included.
Huw W. Lewis, Juan Manuel Castillo Sanchez, Alex Arnold, Joachim Fallmann, Andrew Saulter, Jennifer Graham, Mike Bush, John Siddorn, Tamzin Palmer, Adrian Lock, John Edwards, Lucy Bricheno, Alberto Martínez-de la Torre, and James Clark
Geosci. Model Dev., 12, 2357–2400, https://doi.org/10.5194/gmd-12-2357-2019, https://doi.org/10.5194/gmd-12-2357-2019, 2019
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In the real world the atmosphere, oceans and land surface are closely interconnected, and yet the prediction systems used for weather and ocean forecasting tend to treat them in isolation. This paper describes the third version of a regional modelling system which aims to represent the feedback processes between sky, sea and land. The main innovation introduced in this version enables waves to affect the underlying ocean. Coupled results from four different month-long simulations are analysed.
Huw W. Lewis, Juan Manuel Castillo Sanchez, John Siddorn, Robert R. King, Marina Tonani, Andrew Saulter, Peter Sykes, Anne-Christine Pequignet, Graham P. Weedon, Tamzin Palmer, Joanna Staneva, and Lucy Bricheno
Ocean Sci., 15, 669–690, https://doi.org/10.5194/os-15-669-2019, https://doi.org/10.5194/os-15-669-2019, 2019
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Forecasts of ocean temperature, salinity, currents, and sea height can be improved by linking state-of-the-art ocean and wave models, so that they can interact to better represent the real world. We test this approach in an ocean model of north-west Europe which can simulate small-scale details of the ocean state. The intention is to implement the system described in this study for operational use so that improved information can be provided to users of ocean forecast data.
David Walters, Anthony J. Baran, Ian Boutle, Malcolm Brooks, Paul Earnshaw, John Edwards, Kalli Furtado, Peter Hill, Adrian Lock, James Manners, Cyril Morcrette, Jane Mulcahy, Claudio Sanchez, Chris Smith, Rachel Stratton, Warren Tennant, Lorenzo Tomassini, Kwinten Van Weverberg, Simon Vosper, Martin Willett, Jo Browse, Andrew Bushell, Kenneth Carslaw, Mohit Dalvi, Richard Essery, Nicola Gedney, Steven Hardiman, Ben Johnson, Colin Johnson, Andy Jones, Colin Jones, Graham Mann, Sean Milton, Heather Rumbold, Alistair Sellar, Masashi Ujiie, Michael Whitall, Keith Williams, and Mohamed Zerroukat
Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, https://doi.org/10.5194/gmd-12-1909-2019, 2019
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Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of JULES are developed for use in any global atmospheric modelling application. We describe a recent iteration of these configurations, GA7/GL7, which includes new aerosol and snow schemes and addresses the four critical errors identified in GA6. GA7/GL7 will underpin the UK's contributions to CMIP6, and hence their documentation is important.
Jennifer K. Brooke, R. Chawn Harlow, Russell L. Scott, Martin J. Best, John M. Edwards, Jean-Claude Thelen, and Mark Weeks
Geosci. Model Dev., 12, 1703–1724, https://doi.org/10.5194/gmd-12-1703-2019, https://doi.org/10.5194/gmd-12-1703-2019, 2019
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This paper evaluates a significant cold land surface temperature bias in semi-arid regions in the Met Office Unified Model when compared with satellite observations. Sparse vegetation canopies are not well represented in ancillary datasets, in particular regions of cold bias are correlated with low bare soil cover fractions. The study demonstrates the difficulties in modelling land surface temperatures that match state-of-the-art satellite retrievals required for operational data assimilation.
Joanne Williams, Maialen Irazoqui Apecechea, Andrew Saulter, and Kevin J. Horsburgh
Ocean Sci., 14, 1057–1068, https://doi.org/10.5194/os-14-1057-2018, https://doi.org/10.5194/os-14-1057-2018, 2018
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Tide predictions based on tide-gauge observations are not just astronomical tides; they also contain periodic sea level changes due to the weather. Forecasts of total water level during storm surges add the immediate effects of the weather to the astronomical tide prediction and thus risk double-counting these effects. We use a global model to see how much double-counting may affect these forecasts and also how much of the Highest Astronomical Tide may be due to recurrent weather patterns.
Claudia Christine Stephan, Nicholas P. Klingaman, Pier Luigi Vidale, Andrew G. Turner, Marie-Estelle Demory, and Liang Guo
Geosci. Model Dev., 11, 3215–3233, https://doi.org/10.5194/gmd-11-3215-2018, https://doi.org/10.5194/gmd-11-3215-2018, 2018
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Summer precipitation over China in the MetUM reaches twice its observed values. Increasing the horizontal resolution of the model and adding air–sea coupling have little effect on these biases. Nevertheless, MetUM correctly simulates spatial patterns of temporally coherent precipitation and the associated large-scale processes. This suggests that the model may provide useful predictions of summer intraseasonal variability despite the substantial biases in overall intraseasonal variance.
Alexander J. Roberts, Margaret J. Woodage, John H. Marsham, Ellie J. Highwood, Claire L. Ryder, Willie McGinty, Simon Wilson, and Julia Crook
Atmos. Chem. Phys., 18, 9025–9048, https://doi.org/10.5194/acp-18-9025-2018, https://doi.org/10.5194/acp-18-9025-2018, 2018
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The summer Saharan dust hotspot is seasonally tied to the occurrence of convective storms. Global weather and climate models parameterise convection and so are unable to represent their associated dust uplift (haboobs). However, this work shows that even when simulations represent convection explicitly: (1) dust fields are not strongly affected, (2) convective storms are too small, (3) haboobs are too weak and (4) the land surface (bare soil and soil moisture) is dominant in controlling dust.
Claudia Christine Stephan, Nicholas P. Klingaman, Pier Luigi Vidale, Andrew G. Turner, Marie-Estelle Demory, and Liang Guo
Geosci. Model Dev., 11, 1823–1847, https://doi.org/10.5194/gmd-11-1823-2018, https://doi.org/10.5194/gmd-11-1823-2018, 2018
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Climate simulations are evaluated for their ability to reproduce year-to-year variability of precipitation over China. Mean precipitation and variability are too high in all simulations but improve with finer resolution and coupling. Simulations reproduce the observed spatial patterns of rainfall variability. However, not all of these patterns are associated with observed mechanisms. For example, simulations do not reproduce summer rainfall along the Yangtze valley in response to El Niño.
Jennifer A. Graham, Enda O'Dea, Jason Holt, Jeff Polton, Helene T. Hewitt, Rachel Furner, Karen Guihou, Ashley Brereton, Alex Arnold, Sarah Wakelin, Juan Manuel Castillo Sanchez, and C. Gabriela Mayorga Adame
Geosci. Model Dev., 11, 681–696, https://doi.org/10.5194/gmd-11-681-2018, https://doi.org/10.5194/gmd-11-681-2018, 2018
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This paper describes the next-generation ocean forecast model for the European NW shelf, AMM15 (Atlantic Margin Model, 1.5 km resolution). The current forecast system has a resolution of 7 km. While this is sufficient to represent large-scale circulation, many dynamical features (such as eddies, frontal jets, and internal tides) can only begin to be resolved at 0–1 km resolution. Here we introduce AMM15 and demonstrate its ability to represent the mean state and variability of the region.
Huw W. Lewis, Juan Manuel Castillo Sanchez, Jennifer Graham, Andrew Saulter, Jorge Bornemann, Alex Arnold, Joachim Fallmann, Chris Harris, David Pearson, Steven Ramsdale, Alberto Martínez-de la Torre, Lucy Bricheno, Eleanor Blyth, Victoria A. Bell, Helen Davies, Toby R. Marthews, Clare O'Neill, Heather Rumbold, Enda O'Dea, Ashley Brereton, Karen Guihou, Adrian Hines, Momme Butenschon, Simon J. Dadson, Tamzin Palmer, Jason Holt, Nick Reynard, Martin Best, John Edwards, and John Siddorn
Geosci. Model Dev., 11, 1–42, https://doi.org/10.5194/gmd-11-1-2018, https://doi.org/10.5194/gmd-11-1-2018, 2018
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In the real world the atmosphere, oceans and land surface are closely interconnected, and yet prediction systems tend to treat them in isolation. Those feedbacks are often illustrated in natural hazards, such as when strong winds lead to large waves and coastal damage, or when prolonged rainfall leads to saturated ground and high flowing rivers. For the first time, we have attempted to represent some of the feedbacks between sky, sea and land within a high-resolution forecast system for the UK.
David Walters, Ian Boutle, Malcolm Brooks, Thomas Melvin, Rachel Stratton, Simon Vosper, Helen Wells, Keith Williams, Nigel Wood, Thomas Allen, Andrew Bushell, Dan Copsey, Paul Earnshaw, John Edwards, Markus Gross, Steven Hardiman, Chris Harris, Julian Heming, Nicholas Klingaman, Richard Levine, James Manners, Gill Martin, Sean Milton, Marion Mittermaier, Cyril Morcrette, Thomas Riddick, Malcolm Roberts, Claudio Sanchez, Paul Selwood, Alison Stirling, Chris Smith, Dan Suri, Warren Tennant, Pier Luigi Vidale, Jonathan Wilkinson, Martin Willett, Steve Woolnough, and Prince Xavier
Geosci. Model Dev., 10, 1487–1520, https://doi.org/10.5194/gmd-10-1487-2017, https://doi.org/10.5194/gmd-10-1487-2017, 2017
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Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of JULES are developed for use in any global atmospheric modelling application.
We describe a recent iteration of these configurations: GA6/GL6. This includes ENDGame: a new dynamical core designed to improve the model's accuracy, stability and scalability. GA6 is now operational in a variety of Met Office and UM collaborators applications and hence its documentation is important.
We describe a recent iteration of these configurations: GA6/GL6. This includes ENDGame: a new dynamical core designed to improve the model's accuracy, stability and scalability. GA6 is now operational in a variety of Met Office and UM collaborators applications and hence its documentation is important.
Emma L. Robinson, Eleanor M. Blyth, Douglas B. Clark, Jon Finch, and Alison C. Rudd
Hydrol. Earth Syst. Sci., 21, 1189–1224, https://doi.org/10.5194/hess-21-1189-2017, https://doi.org/10.5194/hess-21-1189-2017, 2017
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We present a dataset of daily meteorological variables at 1 km resolution over Great Britain (1961–2012), calculated by spatially downscaling coarser resolution datasets, adjusting for local topography, along with derived potential evapotranspiration (PET). A positive trend in PET was identified and attributed to trends in the meteorology. The trend in PET is particularly driven by decreasing relative humidity and increasing shortwave radiation in the spring.
Stephen M. Griffies, Gokhan Danabasoglu, Paul J. Durack, Alistair J. Adcroft, V. Balaji, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Julie Deshayes, Helge Drange, Baylor Fox-Kemper, Peter J. Gleckler, Jonathan M. Gregory, Helmuth Haak, Robert W. Hallberg, Patrick Heimbach, Helene T. Hewitt, David M. Holland, Tatiana Ilyina, Johann H. Jungclaus, Yoshiki Komuro, John P. Krasting, William G. Large, Simon J. Marsland, Simona Masina, Trevor J. McDougall, A. J. George Nurser, James C. Orr, Anna Pirani, Fangli Qiao, Ronald J. Stouffer, Karl E. Taylor, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Maria Valdivieso, Qiang Wang, Michael Winton, and Stephen G. Yeager
Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, https://doi.org/10.5194/gmd-9-3231-2016, 2016
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The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This document defines OMIP and details a protocol both for simulating global ocean/sea-ice models and for analysing their output.
Heather Cannaby, Matthew D. Palmer, Tom Howard, Lucy Bricheno, Daley Calvert, Justin Krijnen, Richard Wood, Jonathan Tinker, Chris Bunney, James Harle, Andrew Saulter, Clare O'Neill, Clare Bellingham, and Jason Lowe
Ocean Sci., 12, 613–632, https://doi.org/10.5194/os-12-613-2016, https://doi.org/10.5194/os-12-613-2016, 2016
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The Singapore government commissioned a modelling study of regional projections of changes in (i) long-term mean sea level and (ii) the frequency of extreme storm surge and wave events. We find that changes to long-term mean sea level constitute the dominant signal of change to the projected inundation risk for Singapore during the 21st century, these being 0.52 m(0.74 m) under the RCP 4.5(8.5) scenario.
J. R. Siddorn, S. A. Good, C. M. Harris, H. W. Lewis, J. Maksymczuk, M. J. Martin, and A. Saulter
Ocean Sci., 12, 217–231, https://doi.org/10.5194/os-12-217-2016, https://doi.org/10.5194/os-12-217-2016, 2016
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The Met Office provides a range of services in the marine environment. To support these services, and to ensure they evolve to meet the demands of users and are based on the best available science, a number of scientific challenges need to be addressed. The paper summarises the key challenges, and highlights some priorities for the ocean monitoring and forecasting research group at the Met Office.
K. Frieler, A. Levermann, J. Elliott, J. Heinke, A. Arneth, M. F. P. Bierkens, P. Ciais, D. B. Clark, D. Deryng, P. Döll, P. Falloon, B. Fekete, C. Folberth, A. D. Friend, C. Gellhorn, S. N. Gosling, I. Haddeland, N. Khabarov, M. Lomas, Y. Masaki, K. Nishina, K. Neumann, T. Oki, R. Pavlick, A. C. Ruane, E. Schmid, C. Schmitz, T. Stacke, E. Stehfest, Q. Tang, D. Wisser, V. Huber, F. Piontek, L. Warszawski, J. Schewe, H. Lotze-Campen, and H. J. Schellnhuber
Earth Syst. Dynam., 6, 447–460, https://doi.org/10.5194/esd-6-447-2015, https://doi.org/10.5194/esd-6-447-2015, 2015
K. Nishina, A. Ito, P. Falloon, A. D. Friend, D. J. Beerling, P. Ciais, D. B. Clark, R. Kahana, E. Kato, W. Lucht, M. Lomas, R. Pavlick, S. Schaphoff, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 6, 435–445, https://doi.org/10.5194/esd-6-435-2015, https://doi.org/10.5194/esd-6-435-2015, 2015
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Our study focused on uncertainties in terrestrial C cycling under newly developed scenarios with CMIP5. This study presents first results for examining relative uncertainties of projected terrestrial C cycling in multiple projection components. Only using our new model inter-comparison project data sets enables us to evaluate various uncertainty sources in projection periods. The information on relative uncertainties is useful for climate science and climate change impact evaluation.
K. D. Williams, C. M. Harris, A. Bodas-Salcedo, J. Camp, R. E. Comer, D. Copsey, D. Fereday, T. Graham, R. Hill, T. Hinton, P. Hyder, S. Ineson, G. Masato, S. F. Milton, M. J. Roberts, D. P. Rowell, C. Sanchez, A. Shelly, B. Sinha, D. N. Walters, A. West, T. Woollings, and P. K. Xavier
Geosci. Model Dev., 8, 1509–1524, https://doi.org/10.5194/gmd-8-1509-2015, https://doi.org/10.5194/gmd-8-1509-2015, 2015
I. D. Culverwell, H. W. Lewis, D. Offiler, C. Marquardt, and C. P. Burrows
Atmos. Meas. Tech., 8, 1887–1899, https://doi.org/10.5194/amt-8-1887-2015, https://doi.org/10.5194/amt-8-1887-2015, 2015
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This paper describes the Radio Occultation Processing Package, ROPP, which is a suite of freely available programs provided by EUMETSAT for the processing of radio occultation data. Its capabilities are briefly reviewed, and examples of its use are given. Some current and prospective uses of ROPP are listed.
L. C. Hirons, N. P. Klingaman, and S. J. Woolnough
Geosci. Model Dev., 8, 363–379, https://doi.org/10.5194/gmd-8-363-2015, https://doi.org/10.5194/gmd-8-363-2015, 2015
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Atmosphere-ocean interactions are best isolated in models rather than observations, but state-of-the-art models are expensive and often simulate these interactions poorly. We present a less expensive modelling framework that resolves air-sea interactions well, and permits a more rigorous identification of these interactions' effects than previously possible. In our model, air-sea interactions improve tropical rainfall variations but have limited effects on midlatitude jet streams.
G. D. Hayman, F. M. O'Connor, M. Dalvi, D. B. Clark, N. Gedney, C. Huntingford, C. Prigent, M. Buchwitz, O. Schneising, J. P. Burrows, C. Wilson, N. Richards, and M. Chipperfield
Atmos. Chem. Phys., 14, 13257–13280, https://doi.org/10.5194/acp-14-13257-2014, https://doi.org/10.5194/acp-14-13257-2014, 2014
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Globally, wetlands are a major source of methane, which is the second most important greenhouse gas. We find the JULES wetland methane scheme to perform well in general, although there is a tendency for it to overpredict emissions in the tropics and underpredict them in northern latitudes. Our study highlights novel uses of satellite data as a major tool to constrain land-atmosphere methane flux models in a warming world.
S. J. O'Shea, G. Allen, M. W. Gallagher, K. Bower, S. M. Illingworth, J. B. A. Muller, B. T. Jones, C. J. Percival, S. J-B. Bauguitte, M. Cain, N. Warwick, A. Quiquet, U. Skiba, J. Drewer, K. Dinsmore, E. G. Nisbet, D. Lowry, R. E. Fisher, J. L. France, M. Aurela, A. Lohila, G. Hayman, C. George, D. B. Clark, A. J. Manning, A. D. Friend, and J. Pyle
Atmos. Chem. Phys., 14, 13159–13174, https://doi.org/10.5194/acp-14-13159-2014, https://doi.org/10.5194/acp-14-13159-2014, 2014
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This paper presents airborne measurements of greenhouse gases collected in the European Arctic. Regional scale flux estimates for the northern Scandinavian wetlands are derived. These fluxes are found to be in excellent agreement with coincident surface measurements within the aircraft's sampling domain. This has allowed a significant low bias to be identified in two commonly used process-based land surface models.
K. Nishina, A. Ito, D. J. Beerling, P. Cadule, P. Ciais, D. B. Clark, P. Falloon, A. D. Friend, R. Kahana, E. Kato, R. Keribin, W. Lucht, M. Lomas, T. T. Rademacher, R. Pavlick, S. Schaphoff, N. Vuichard, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 5, 197–209, https://doi.org/10.5194/esd-5-197-2014, https://doi.org/10.5194/esd-5-197-2014, 2014
D. N. Walters, K. D. Williams, I. A. Boutle, A. C. Bushell, J. M. Edwards, P. R. Field, A. P. Lock, C. J. Morcrette, R. A. Stratton, J. M. Wilkinson, M. R. Willett, N. Bellouin, A. Bodas-Salcedo, M. E. Brooks, D. Copsey, P. D. Earnshaw, S. C. Hardiman, C. M. Harris, R. C. Levine, C. MacLachlan, J. C. Manners, G. M. Martin, S. F. Milton, M. D. Palmer, M. J. Roberts, J. M. Rodríguez, W. J. Tennant, and P. L. Vidale
Geosci. Model Dev., 7, 361–386, https://doi.org/10.5194/gmd-7-361-2014, https://doi.org/10.5194/gmd-7-361-2014, 2014
J. C. S. Davie, P. D. Falloon, R. Kahana, R. Dankers, R. Betts, F. T. Portmann, D. Wisser, D. B. Clark, A. Ito, Y. Masaki, K. Nishina, B. Fekete, Z. Tessler, Y. Wada, X. Liu, Q. Tang, S. Hagemann, T. Stacke, R. Pavlick, S. Schaphoff, S. N. Gosling, W. Franssen, and N. Arnell
Earth Syst. Dynam., 4, 359–374, https://doi.org/10.5194/esd-4-359-2013, https://doi.org/10.5194/esd-4-359-2013, 2013
S. Hagemann, C. Chen, D. B. Clark, S. Folwell, S. N. Gosling, I. Haddeland, N. Hanasaki, J. Heinke, F. Ludwig, F. Voss, and A. J. Wiltshire
Earth Syst. Dynam., 4, 129–144, https://doi.org/10.5194/esd-4-129-2013, https://doi.org/10.5194/esd-4-129-2013, 2013
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How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
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Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
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Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
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An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
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Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
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A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
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In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Gerrit Kuhlmann, Erik F. M. Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2936, https://doi.org/10.5194/egusphere-2023-2936, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter Notebooks included in the library.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-234, https://doi.org/10.5194/gmd-2023-234, 2024
Revised manuscript accepted for GMD
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air quality-challenged arid/semi-arid region in the US. The unique characteristics of semi-arid/arid regions, e.g., intense heat, minimal moisture, persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure facilitating further processing to allow emission processing from continental to street scale.
Najmeh Kaffashzadeh and Abbas Ali Aliakbari Bidokhti
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-226, https://doi.org/10.5194/gmd-2023-226, 2024
Revised manuscript accepted for GMD
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Reanalysis data have been widely used as an initial condition for the daily forecast of the atmosphere or boundary conditions in regional models, for the study of climate change, and as proxies to complement insufficient in situ measurements. This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2023-2962, https://doi.org/10.5194/egusphere-2023-2962, 2024
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There are relatively limited researches on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPU, have distinct advantages in energy efficiency and scalability. In this study, the air quality modeling system can run stably on MIPS CPU platform, and the experiment results verify the stability of scientific computing on the platform. The work provides a technical foundation for the scientific application based on MIPS CPU platforms.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
Short summary
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
Short summary
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
Short summary
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-209, https://doi.org/10.5194/gmd-2023-209, 2023
Revised manuscript accepted for GMD
Short summary
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This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-202, https://doi.org/10.5194/gmd-2023-202, 2023
Revised manuscript accepted for GMD
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Global Navigation Satellite Systems provide moisture observations through its densely distributed ground station network. In this research, we assimilated a new type of observation called tropospheric gradient observations, which was never incorporated into a weather model. Here, we have developed a forward operator for gradient observations and performed impact studies. Promising improvements were observed in the humidity fields of the model in the assimilation study.
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Short summary
A new environmental modelling system has been developed to represent the effect of feedbacks between atmosphere, land, and ocean in the Indian region. Different approaches to simulating tropical cyclones Titli and Fani are demonstrated. It is shown that results are sensitive to the way in which the ocean response to cyclone evolution is captured in the system. Notably, we show how a more rigorous formulation for the near-surface energy budget can be included when air–sea coupling is included.
A new environmental modelling system has been developed to represent the effect of feedbacks...