Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7705-2021
© Author(s) 2021. 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-14-7705-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Non-Hydrostatic RegCM4 (RegCM4-NH): model description and case studies over multiple domains
Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy
Paolo Stocchi
Institute of Atmospheric Sciences and Climate, National Research Council of Italy, CNR-ISAC, Bologna, Italy
Emanuela Pichelli
Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy
Jose Abraham Torres Alavez
Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy
Russell Glazer
Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy
Graziano Giuliani
Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy
Fabio Di Sante
Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy
Rita Nogherotto
Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy
Filippo Giorgi
Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy
Related authors
Davide Faranda, Gabriele Messori, Erika Coppola, Tommaso Alberti, Mathieu Vrac, Flavio Pons, Pascal Yiou, Marion Saint Lu, Andreia N. S. Hisi, Patrick Brockmann, Stavros Dafis, and Robert Vautard
EGUsphere, https://doi.org/10.5194/egusphere-2023-2643, https://doi.org/10.5194/egusphere-2023-2643, 2023
Short summary
Short summary
We introduce ClimaMeter, a tool offering real-time insights into weather extreme events. Our tool unveils how climate change and natural variability affect these events, affecting communities worldwide. Our research equips policymakers and the public with essential knowledge, fostering informed decisions and enhancing climate resilience. We analyzed four distinct events, showcasing ClimaMeter's global relevance.
Susanna Strada, Andrea Pozzer, Graziano Giuliani, Erika Coppola, Fabien Solmon, Xiaoyan Jiang, Alex Guenther, Efstratios Bourtsoukidis, Dominique Serça, Jonathan Williams, and Filippo Giorgi
Atmos. Chem. Phys., 23, 13301–13327, https://doi.org/10.5194/acp-23-13301-2023, https://doi.org/10.5194/acp-23-13301-2023, 2023
Short summary
Short summary
Water deficit modifies emissions of isoprene, an aromatic compound released by plants that influences the production of an air pollutant such as ozone. Numerical modelling shows that, during the warmest and driest summers, isoprene decreases between −20 and −60 % over the Euro-Mediterranean region, while near-surface ozone only diminishes by a few percent. Decreases in isoprene emissions not only happen under dry conditions, but also could occur after prolonged or repeated water deficits.
Edouard L. Davin, Diana Rechid, Marcus Breil, Rita M. Cardoso, Erika Coppola, Peter Hoffmann, Lisa L. Jach, Eleni Katragkou, Nathalie de Noblet-Ducoudré, Kai Radtke, Mario Raffa, Pedro M. M. Soares, Giannis Sofiadis, Susanna Strada, Gustav Strandberg, Merja H. Tölle, Kirsten Warrach-Sagi, and Volker Wulfmeyer
Earth Syst. Dynam., 11, 183–200, https://doi.org/10.5194/esd-11-183-2020, https://doi.org/10.5194/esd-11-183-2020, 2020
Rita Nogherotto, Adriano Fantini, Francesca Raffaele, Fabio Di Sante, Francesco Dottori, Erika Coppola, and Filippo Giorgi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2019-356, https://doi.org/10.5194/nhess-2019-356, 2019
Revised manuscript not accepted
Filippo Giorgi, Francesca Raffaele, and Erika Coppola
Earth Syst. Dynam., 10, 73–89, https://doi.org/10.5194/esd-10-73-2019, https://doi.org/10.5194/esd-10-73-2019, 2019
Short summary
Short summary
The paper revisits the critical issue of precipitation characteristics in response to global warming through a new analysis of global and regional climate projections and a summary of previous work. Robust responses are identified and the underlying processes investigated. Examples of applications are given, such as the evaluation of risks associated with extremes. The paper, solicited by the EGU executive office, is based on the 2018 EGU Alexander von Humboldt medal lecture by Filippo Giorgi.
Martin Beniston, Daniel Farinotti, Markus Stoffel, Liss M. Andreassen, Erika Coppola, Nicolas Eckert, Adriano Fantini, Florie Giacona, Christian Hauck, Matthias Huss, Hendrik Huwald, Michael Lehning, Juan-Ignacio López-Moreno, Jan Magnusson, Christoph Marty, Enrique Morán-Tejéda, Samuel Morin, Mohamed Naaim, Antonello Provenzale, Antoine Rabatel, Delphine Six, Johann Stötter, Ulrich Strasser, Silvia Terzago, and Christian Vincent
The Cryosphere, 12, 759–794, https://doi.org/10.5194/tc-12-759-2018, https://doi.org/10.5194/tc-12-759-2018, 2018
Short summary
Short summary
This paper makes a rather exhaustive overview of current knowledge of past, current, and future aspects of cryospheric issues in continental Europe and makes a number of reflections of areas of uncertainty requiring more attention in both scientific and policy terms. The review paper is completed by a bibliography containing 350 recent references that will certainly be of value to scholars engaged in the fields of glacier, snow, and permafrost research.
Rita Nogherotto, Adrian Mark Tompkins, Graziano Giuliani, Erika Coppola, and Filippo Giorgi
Geosci. Model Dev., 9, 2533–2547, https://doi.org/10.5194/gmd-9-2533-2016, https://doi.org/10.5194/gmd-9-2533-2016, 2016
Short summary
Short summary
The paper presents a new cloud scheme for regional climate model RegCM4.5. The new scheme treats microphysical processes occurring within stratiform clouds and with respect to the pre-existing scheme is able to allow a more physically realistic representation of cloud microphysics and distribution, improving the representation of the longwave and shortwave components of the cloud radiative forcing.
M. A. H. Zaroug, F. Giorgi, E. Coppola, G. M. Abdo, and E. A. B. Eltahir
Hydrol. Earth Syst. Sci., 18, 4311–4323, https://doi.org/10.5194/hess-18-4311-2014, https://doi.org/10.5194/hess-18-4311-2014, 2014
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Davide Faranda, Gabriele Messori, Erika Coppola, Tommaso Alberti, Mathieu Vrac, Flavio Pons, Pascal Yiou, Marion Saint Lu, Andreia N. S. Hisi, Patrick Brockmann, Stavros Dafis, and Robert Vautard
EGUsphere, https://doi.org/10.5194/egusphere-2023-2643, https://doi.org/10.5194/egusphere-2023-2643, 2023
Short summary
Short summary
We introduce ClimaMeter, a tool offering real-time insights into weather extreme events. Our tool unveils how climate change and natural variability affect these events, affecting communities worldwide. Our research equips policymakers and the public with essential knowledge, fostering informed decisions and enhancing climate resilience. We analyzed four distinct events, showcasing ClimaMeter's global relevance.
Susanna Strada, Andrea Pozzer, Graziano Giuliani, Erika Coppola, Fabien Solmon, Xiaoyan Jiang, Alex Guenther, Efstratios Bourtsoukidis, Dominique Serça, Jonathan Williams, and Filippo Giorgi
Atmos. Chem. Phys., 23, 13301–13327, https://doi.org/10.5194/acp-23-13301-2023, https://doi.org/10.5194/acp-23-13301-2023, 2023
Short summary
Short summary
Water deficit modifies emissions of isoprene, an aromatic compound released by plants that influences the production of an air pollutant such as ozone. Numerical modelling shows that, during the warmest and driest summers, isoprene decreases between −20 and −60 % over the Euro-Mediterranean region, while near-surface ozone only diminishes by a few percent. Decreases in isoprene emissions not only happen under dry conditions, but also could occur after prolonged or repeated water deficits.
Costanza Del Gobbo, Renato R. Colucci, Giovanni Monegato, Manja Žebre, and Filippo Giorgi
Clim. Past, 19, 1805–1823, https://doi.org/10.5194/cp-19-1805-2023, https://doi.org/10.5194/cp-19-1805-2023, 2023
Short summary
Short summary
We studied atmosphere–cryosphere interaction during the last phase of the Last Glacial Maximum in the Alpine region, using a high-resolution regional climate model. We analysed the climate south and north of the Alps, using a detailed map of the Alpine equilibrium line altitude (ELA) to study the mechanism that sustained the Alpine glaciers at 21 ka. The Genoa low and a mild Mediterranean Sea led to frequent snowfall in the southern Alps, thus preserving the glaciers and lowering the ELA.
Sudipta Ghosh, Sagnik Dey, Sushant Das, Nicole Riemer, Graziano Giuliani, Dilip Ganguly, Chandra Venkataraman, Filippo Giorgi, Sachchida Nand Tripathi, Srikanthan Ramachandran, Thazhathakal Ayyappen Rajesh, Harish Gadhavi, and Atul Kumar Srivastava
Geosci. Model Dev., 16, 1–15, https://doi.org/10.5194/gmd-16-1-2023, https://doi.org/10.5194/gmd-16-1-2023, 2023
Short summary
Short summary
Accurate representation of aerosols in climate models is critical for minimizing the uncertainty in climate projections. Here, we implement region-specific emission fluxes and a more accurate scheme for carbonaceous aerosol ageing processes in a regional climate model (RegCM4) and show that it improves model performance significantly against in situ, reanalysis, and satellite data over the Indian subcontinent. We recommend improving the model performance before using them for climate studies.
Vijayakumar Sivadasan Nair, Filippo Giorgi, and Usha Keshav Hasyagar
Atmos. Chem. Phys., 20, 14457–14471, https://doi.org/10.5194/acp-20-14457-2020, https://doi.org/10.5194/acp-20-14457-2020, 2020
Short summary
Short summary
Air pollution and wintertime fog over South Asia is a major concern due to its significant implications on air quality, visibility and health. Coupled model simulations show that hygroscopic growth of aerosols contributes significantly to the aerosol-induced cooling at the surface. Our analysis demonstrates that the aerosol–moisture interaction is the most significant contributor favouring and strengthening the high-aerosol conditions (poor air quality) prevailing over South Asia during winter.
Edouard L. Davin, Diana Rechid, Marcus Breil, Rita M. Cardoso, Erika Coppola, Peter Hoffmann, Lisa L. Jach, Eleni Katragkou, Nathalie de Noblet-Ducoudré, Kai Radtke, Mario Raffa, Pedro M. M. Soares, Giannis Sofiadis, Susanna Strada, Gustav Strandberg, Merja H. Tölle, Kirsten Warrach-Sagi, and Volker Wulfmeyer
Earth Syst. Dynam., 11, 183–200, https://doi.org/10.5194/esd-11-183-2020, https://doi.org/10.5194/esd-11-183-2020, 2020
Rita Nogherotto, Adriano Fantini, Francesca Raffaele, Fabio Di Sante, Francesco Dottori, Erika Coppola, and Filippo Giorgi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2019-356, https://doi.org/10.5194/nhess-2019-356, 2019
Revised manuscript not accepted
Filippo Giorgi, Francesca Raffaele, and Erika Coppola
Earth Syst. Dynam., 10, 73–89, https://doi.org/10.5194/esd-10-73-2019, https://doi.org/10.5194/esd-10-73-2019, 2019
Short summary
Short summary
The paper revisits the critical issue of precipitation characteristics in response to global warming through a new analysis of global and regional climate projections and a summary of previous work. Robust responses are identified and the underlying processes investigated. Examples of applications are given, such as the evaluation of risks associated with extremes. The paper, solicited by the EGU executive office, is based on the 2018 EGU Alexander von Humboldt medal lecture by Filippo Giorgi.
Brahima Koné, Arona Diedhiou, N'datchoh Evelyne Touré, Mouhamadou Bamba Sylla, Filippo Giorgi, Sandrine Anquetin, Adama Bamba, Adama Diawara, and Arsene Toka Kobea
Earth Syst. Dynam., 9, 1261–1278, https://doi.org/10.5194/esd-9-1261-2018, https://doi.org/10.5194/esd-9-1261-2018, 2018
Short summary
Short summary
Simulations of regional climate are very sensitive to physical parameterization schemes, particularly over the tropics where convection plays a major role in monsoon dynamics. The latest version of RegCM4 was used to assess the performance and sensitivity of the simulated West African climate system to different convection schemes. The configuration of RegCM4 with CLM4.5 as a land surface model and the Emanuel convective scheme is recommended for the study of the West African climate.
Martin Beniston, Daniel Farinotti, Markus Stoffel, Liss M. Andreassen, Erika Coppola, Nicolas Eckert, Adriano Fantini, Florie Giacona, Christian Hauck, Matthias Huss, Hendrik Huwald, Michael Lehning, Juan-Ignacio López-Moreno, Jan Magnusson, Christoph Marty, Enrique Morán-Tejéda, Samuel Morin, Mohamed Naaim, Antonello Provenzale, Antoine Rabatel, Delphine Six, Johann Stötter, Ulrich Strasser, Silvia Terzago, and Christian Vincent
The Cryosphere, 12, 759–794, https://doi.org/10.5194/tc-12-759-2018, https://doi.org/10.5194/tc-12-759-2018, 2018
Short summary
Short summary
This paper makes a rather exhaustive overview of current knowledge of past, current, and future aspects of cryospheric issues in continental Europe and makes a number of reflections of areas of uncertainty requiring more attention in both scientific and policy terms. The review paper is completed by a bibliography containing 350 recent references that will certainly be of value to scholars engaged in the fields of glacier, snow, and permafrost research.
William J. Gutowski Jr., Filippo Giorgi, Bertrand Timbal, Anne Frigon, Daniela Jacob, Hyun-Suk Kang, Krishnan Raghavan, Boram Lee, Christopher Lennard, Grigory Nikulin, Eleanor O'Rourke, Michel Rixen, Silvina Solman, Tannecia Stephenson, and Fredolin Tangang
Geosci. Model Dev., 9, 4087–4095, https://doi.org/10.5194/gmd-9-4087-2016, https://doi.org/10.5194/gmd-9-4087-2016, 2016
Short summary
Short summary
The Coordinated Regional Downscaling Experiment (CORDEX) is a diagnostic MIP in CMIP6. CORDEX builds on a foundation of previous downscaling intercomparison projects to provide a common framework for downscaling activities around the world. The CORDEX Regional Challenges provide a focus for downscaling research and a basis for making use of CMIP6 global output to produce downscaled projected changes in regional climates, and assess sources of uncertainties in the projections.
Rita Nogherotto, Adrian Mark Tompkins, Graziano Giuliani, Erika Coppola, and Filippo Giorgi
Geosci. Model Dev., 9, 2533–2547, https://doi.org/10.5194/gmd-9-2533-2016, https://doi.org/10.5194/gmd-9-2533-2016, 2016
Short summary
Short summary
The paper presents a new cloud scheme for regional climate model RegCM4.5. The new scheme treats microphysical processes occurring within stratiform clouds and with respect to the pre-existing scheme is able to allow a more physically realistic representation of cloud microphysics and distribution, improving the representation of the longwave and shortwave components of the cloud radiative forcing.
Li Liu, Fabien Solmon, Robert Vautard, Lynda Hamaoui-Laguel, Csaba Zsolt Torma, and Filippo Giorgi
Biogeosciences, 13, 2769–2786, https://doi.org/10.5194/bg-13-2769-2016, https://doi.org/10.5194/bg-13-2769-2016, 2016
Short summary
Short summary
To study the distribution of airborne ragweed pollen in changing environments and associated health risks over Europe, we introduce an approach with explicit treatment of pollen ripening, release and dispersion due to environmental drivers in an online modelling framework where climate is integrated with dispersion and vegetation production. From a simulated pollen season and concentration pattern health risks are evaluated through calculation of exposure time above health-relevant threshold levels.
P. Stocchi and S. Davolio
Adv. Sci. Res., 13, 7–12, https://doi.org/10.5194/asr-13-7-2016, https://doi.org/10.5194/asr-13-7-2016, 2016
Short summary
Short summary
Three heavy rain events over NE Alps were simulated using a high-resolution model to evaluate the effect of the SST of the Adriatic Sea.
These preliminary results show that SST influences the surface heat fluxes over the sea, but does not necessary affect the vertical integrated water vapour flux across the coast.
The response of heavy precipitation to a SST change is complex: SST affects the PBL characteristics and thus the flow dynamics and its interaction with orography.
H.-W. Jacobi, S. Lim, M. Ménégoz, P. Ginot, P. Laj, P. Bonasoni, P. Stocchi, A. Marinoni, and Y. Arnaud
The Cryosphere, 9, 1685–1699, https://doi.org/10.5194/tc-9-1685-2015, https://doi.org/10.5194/tc-9-1685-2015, 2015
Short summary
Short summary
We detected up to 70 ppb of black carbon (BC) in surface snow in the upper Khumbu Valley, Nepal. With an upgraded snowpack model, including radiative transfer inside the snow, we studied the impact of BC on snow albedo, melting and radiative forcing for the sensitive high altitude regions of the Himalayas. We found that due to BC, the melting of the snow can be shifted by several days up to several weeks depending on meteorological conditions. The impact of BC is larger in dirty snow.
F. Salerno, N. Guyennon, S. Thakuri, G. Viviano, E. Romano, E. Vuillermoz, P. Cristofanelli, P. Stocchi, G. Agrillo, Y. Ma, and G. Tartari
The Cryosphere, 9, 1229–1247, https://doi.org/10.5194/tc-9-1229-2015, https://doi.org/10.5194/tc-9-1229-2015, 2015
Short summary
Short summary
Climate-trends data in Himalaya are completely absent at high elevation. We explore the south slopes of Mt Everest though time series reconstructed from 7 stations (2660-5600m) during 1994-2013. The main increase in temp is concentrated outside of the monsoon, minimum temp increased far more than maximum, while we note a precipitation weakening. We contribute to change the perspective on which climatic drivers (temperature vs. precipitation) led mainly the glacier responses in the last 20 yr.
G. Curci, L. Ferrero, P. Tuccella, F. Barnaba, F. Angelini, E. Bolzacchini, C. Carbone, H. A. C. Denier van der Gon, M. C. Facchini, G. P. Gobbi, J. P. P. Kuenen, T. C. Landi, C. Perrino, M. G. Perrone, G. Sangiorgi, and P. Stocchi
Atmos. Chem. Phys., 15, 2629–2649, https://doi.org/10.5194/acp-15-2629-2015, https://doi.org/10.5194/acp-15-2629-2015, 2015
Short summary
Short summary
Particulate matter (PM) at ground level is of primary concern for the quality of the air we breathe. Most direct sources of PM are near the ground, but an important fraction of PM is produced by photochemical processes happening also in the upper atmospheric layers. We investigated the contribution of those layers to the PM near the ground and found a significant impact. Nitrate is a major player in the “vertical direction”, owing to its sensitivity to ambient temperature and relative humidity.
M. A. H. Zaroug, F. Giorgi, E. Coppola, G. M. Abdo, and E. A. B. Eltahir
Hydrol. Earth Syst. Sci., 18, 4311–4323, https://doi.org/10.5194/hess-18-4311-2014, https://doi.org/10.5194/hess-18-4311-2014, 2014
R. Ferretti, E. Pichelli, S. Gentile, I. Maiello, D. Cimini, S. Davolio, M. M. Miglietta, G. Panegrossi, L. Baldini, F. Pasi, F. S. Marzano, A. Zinzi, S. Mariani, M. Casaioli, G. Bartolini, N. Loglisci, A. Montani, C. Marsigli, A. Manzato, A. Pucillo, M. E. Ferrario, V. Colaiuda, and R. Rotunno
Hydrol. Earth Syst. Sci., 18, 1953–1977, https://doi.org/10.5194/hess-18-1953-2014, https://doi.org/10.5194/hess-18-1953-2014, 2014
M. A. H. Zaroug, E. A. B. Eltahir, and F. Giorgi
Hydrol. Earth Syst. Sci., 18, 1239–1249, https://doi.org/10.5194/hess-18-1239-2014, https://doi.org/10.5194/hess-18-1239-2014, 2014
E. Pichelli, R. Ferretti, M. Cacciani, A. M. Siani, V. Ciardini, and T. Di Iorio
Atmos. Meas. Tech., 7, 315–332, https://doi.org/10.5194/amt-7-315-2014, https://doi.org/10.5194/amt-7-315-2014, 2014
U. U. Turuncoglu, G. Giuliani, N. Elguindi, and F. Giorgi
Geosci. Model Dev., 6, 283–299, https://doi.org/10.5194/gmd-6-283-2013, https://doi.org/10.5194/gmd-6-283-2013, 2013
Related subject area
Climate and Earth system modeling
Parallel SnowModel (v1.0): a parallel implementation of a distributed snow-evolution modeling system (SnowModel)
LB-SCAM: a learning-based method for efficient large-scale sensitivity analysis and tuning of the Single Column Atmosphere Model (SCAM)
Quantifying the impact of SST feedback frequency on Madden–Julian oscillation simulations
Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3
A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate
A radiative–convective model computing precipitation with the maximum entropy production hypothesis
Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0
Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model using WRF–ML v1.0
Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model
cfr (v2024.1.26): a Python package for climate field reconstruction
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1
A comprehensive Earth system model (AWI-ESM2.1) with interactive icebergs: effects on surface and deep-ocean characteristics
The regional climate–chemistry–ecology coupling model RegCM-Chem (v4.6)–YIBs (v1.0): development and application
An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Continental-scale bias-corrected climate and hydrological projections for Australia
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
Multivariate adjustment of drizzle bias using machine learning in European climate projections
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
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
Short summary
Short summary
Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
Short summary
Short summary
To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
Short summary
Short summary
This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
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
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
Short summary
Short summary
Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
Short summary
Short summary
All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
Short summary
Short summary
We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
Short summary
Short summary
In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
Short summary
Short summary
Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
Short summary
Short summary
Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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 driven by either uniform erosion 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.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
Short summary
Short summary
In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
Short summary
Short summary
We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
Short summary
Short summary
Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
Short summary
Short summary
We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
Short summary
Short summary
Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
Short summary
Short summary
Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
Short summary
Short summary
Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
Short summary
Short summary
We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
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.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
EGUsphere, https://doi.org/10.5194/egusphere-2024-45, https://doi.org/10.5194/egusphere-2024-45, 2024
Short summary
Short summary
This study focused on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies were applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method of Random Forest for increasing the accuracy of climate models, concerning the projection of the number of wet days.
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.
Cited articles
Anthes, R. A., Hsie, E.-Y., and Kuo, Y. -H.: Description of the Penn
State/NCAR Mesoscale Model: Version 4 (MM4),
National Center for Atmospheric Research, Boulder, CO, USA, NCAR Techn. Note, 4, 79 pp., NCAR/TN-282+STR, https://doi.org/10.5065/D64B2Z90, 1987.
Anyah, R., Semazzi, F. H. M., and Xie, L.: Simulated Physical Mechanisms
Associated with Climate Variability over Lake Victoria Basin in East Africa,
Mon. Weather Rev., 134, 3588–3609, 2006.
Anyah, R. O. and Semazzi, F.: Idealized simulation of hydrodynamic
characteristics of Lake Victoria that potentially modulate regional climate,
Int. J. Climatol., 29, 971–981, https://doi.org/10.1002/joc.1795, 2009.
Ashouri, H., Hsu, K., Sorooshian, S., Braithwaite, D. K., Knapp, K. R.,
Cecil, L. D., Nelson, B. R., and Prat, O. P.: PERSIANN-CDR: Daily
Precipitation Climate Data Record from Multisatellite Observations for
Hydrological and Climate Studies, Bull. Am. Meteorol. Soc., 96, 69–83, https://doi.org/10.1175/BAMS-D-13-00068.1, 2015.
Ban, N., Schmidli, J., and Schär, C.: Evaluation of the
convection-resolving regional climate modeling approach in decade-long
simulations, J. Geophys. Res.-Atmos., 119, 7889–7907, https://doi.org/10.1002/2014JD021478, 2014.
Ban, N., Schmidli, J., and Schär ,C.: Heavy precipitation
in a changing climate: does short-term summer precipitation increase
faster?, Geophys. Res.-Lett., 42, 1165–1172, https://doi.org/10.1002/2014GL062588, 2015.
Ban, N., Caillaud, C., Coppola, E., Pichelli, E., Sobolowski, S., Adinolfi, M., Ahrens, B., Alias, A., Anders, I., Bastin, S., Belušić, D., Berthou, S., Brisson, E., Cardoso, R. M., Chan, S. C., Bøssing Christensen, O., Fernández, J., Fita, L., Frisius, T., Gašparac, G., Giorgi, F., Goergen, K., Haugen, J. E., Hodnebrog, Ø., Kartsios, S., Katragkou, E., Kendon, E. J., Keuler, K., Lavin-Gullon, A., Lenderink, G., Leutwyler, D., Lorenz, T., Maraun, D., Mercogliano, P., Milovac, J., Panitz, H.-J., Raffa, M., Reca Remedio, A., Schär, C., Soares, P. M. M., Srnec, L., Steensen, B. M., Stocchi, P., Tölle, M. H., Truhetz, H., Vergara-Temprado, J., de Vries, H., Warrach-Sagi, K., Wulfmeyer, V., and Zander, M. J.: The first multi-model ensemble of
regional climate simulations at kilometer-scale resolution, part I:
evaluation of precipitation, Clim. Dynam., 57, 275–302, https://doi.org/10.1007/s00382-021-05708-w, 2021.
Beheng, K.: A parameterization of warm cloud microphysical conversion
processes, Atmos. Res., 33, 193–206, 1994.
Bennington, V., Notaro, M., and Holman, K. D.: Improving Climate Sensitivity
of Deep Lakes within a Regional Climate Model and Its Impact on Simulated
Climate, J. Climl., 27, 2886–2911, 2014.
Bretherton, C. S., McCaa, J. R., and Grenier, H.: A new parameterization for
shallow cumulus convection and its application to marine subtropical
cloud-topped boundary lay-ers. I. Description and 1D results, Mon. Weather
Rev., 132, 864–882, 2004.
Chen, M., Shi, W., Xie, P., Silva, V. B. S., Kousky, V. E., Higgins, R. W., and Janowiak, J. E.: Assessing objective techniques for gauge-based analyses of global daily precipitation, J. Geophys. Res., 113, D04110, https://doi.org/10.1029/2007JD009132, 2008.
Clark, P., Roberts, N., Lean, H., Ballard, S. P., and Charlton-Perez, C.:
Convection-permitting models: A step-change in rainfall forecasting, Meteor.
Appl., 23, 165–181, https://doi.org/10.1002/met.1538, 2016.
Coppola, E., Giorgi, F., Mariotti, L., and Bi, X.: RegT-Band: a tropical band
version of RegCM4, Clim. Res., 52, 115–133, 2012.
Coppola, E., Sobolowski, S., Pichelli, E., Pichelli, E., Raffaele, F., Ahrens, B., Anders, I., Ban, N., Bastin, S., Belda, M., Belusic, D., Caldas-Alvarez, A., Cardoso, R. M., Davolio, S., Dobler, A., Fernandez, J., Fita, L., Fumiere, Q., Giorgi, F., Goergen, K., Güttler, I., Halenka, T., Heinzeller, D., Hodnebrog, Ø., Jacob, D., Kartsios, S., Katragkou, E., Kendon, E, Khodayar, S., Kunstmann, H., Knist, S., Lavín-Gullón, A., Lind, P., Lorenz, T., Maraun, D., Marelle, L., van Meijgaard, E., Milovac, J., Myhre, G., Panitz, H.-J., Piazza, M., Raffa, M., Raub, T., Rockel, B., Schär, C., Sieck, K., Soares, P. M. M., Somot, S., Srnec, L., Stocchi, P., Tölle, M. H., Truhetz, H., Vautard, R., de Vries, H., and Warrach-Sagi, K.: A first-of-its-kind multi-model convection permitting ensemble for investigating convective phenomena over Europe and the Mediterranean, Clim. Dynam., 55, 3–34, https://doi.org/10.1007/s00382-018-4521-8, 2020.
Coppola, E., Stocchi, P., Pichelli, E., Torres, A., Glazer, R., Graziano, G., Di Sante, F., Nogherotto, R., and Giorgi, F.: RegCM-NH namelists for test cases presented in the paper “Non-Hydrostatic RegCM4 (RegCM4-NH): Model description and case studies over multiple domains”, Zenodo [code], https://doi.org/10.5281/zenodo.5106399, 2021.
Dacre, H. F., Clark, P. A., Martinez-Alvarado, O., Stringer, M. A., and
Lavers, D. A.: How do atmospheric rivers form?, Bull. Amer. Meteorol. Soc.,
96, 1243–1255, https://doi.org/10.1175/BAMS-D-14-00031.1, 2015.
Dee, D. P., Källén, E., Simmons, A. J., and Haimberger, L.: Comments on “Reanalyses suitable for characterizing long-term trends”, B. Am. Meteorol. Soc., 92, 65–70, https://doi.org/10.1175/2010BAMS3070.1, 2011.
Diallo, I., Giorgi, F., and Stordal, F.: Influence of Lake Malawi on regional
climate from a double nested regional climate model experiment, Clim. Dynam., 50, 3397–3411, https://doi.org/10.1007/s00382-017-3811-x, 2018.
Dickinson, R. E., Errico, R. M., Giorgi, F., and Bates, G. T.: A regional climate model
for the western United States, Climatic Change, 15, 383–422,
https://doi.org/10.1007/BF00240465, 1989.
Dickinson, R. E., Henderson-Sellers, A., and Kennedy, P.: Biosphere–atmosphere transfer scheme (BATS) version 1e as coupled to the NCAR community climate model, TechRep, National Center for Atmospheric Research, Boulder, CO, USA, 80 pp., NCAR.TN-387+STR, 1993.
Done, J., Davis, C. A., and Weisman M. L.: The next generation of NWP:
Explicit forecasts of convection using the Weather Research and Forecasting
(WRF) model, Atmos. Sci. Lett., 5, 110–117, https://doi.org/10.1002/asl.72,
2004.
Dudhia, J.: Numerical study of convection observed during the winter monsoon
experiment using a mesoscale two-dimensional model, J. Atmos. Sci., 46,
3077–3107, 1989.
Durran, D. R. and Klemp, J. B.: A compressible model for the simulation of
moist mountain waves, Mon. Weather Rev., 111, 2341–2361, 1983.
Elguindi, N., Bi, X., Giorgi, F., Nagarajan, B., Pal, J., Solmon, F.,
Rauscher, S., Zakey, S., O'Brien, T., Nogherotto, R., and Giuliani, G.:
Regional Climate Model, RegCM Reference Manual Version 4.7, 49 pp., https://zenodo.org/record/4603616, 2017.
Emanuel, K. A.: A scheme for representing cumulus convection in large-scale
models, J. Atmos. Sci, 48, 2313–2335, 1991.
Fairall, C. W., Bradley, E. F., Godfrey, J. S., Wick, G. A., Edson, J. B., and Young, G. S.: The cool skin and the warm layer in bulk flux calculations, J. Geophys. Res., 101, 1295–1308, 1996a.
Fairall, C. W., Bradley, E. F., Rogers, D. P., Edson, J. B., and Young, G. S.: Bulk parameterization of air-sea fluxes for TOGA COARE, J. Geophys. Res.,
101, 3747–3764, 1996b.
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J.: The climate hazards infrared
precipitation with stations–a new environmental record for monitoring
extremes, Sci. Data, 2, 150066, https://doi.org/10.1038/sdata.2015.66, 2015.
Gimeno, L., Nieto, R., Vaìsquez, M., and Lavers, D. A.: Atmospheric rivers: A mini-review, Front. Earth Sci., 2, 1–6, https://doi.org/10.3389/feart.2014.00002, 2014.
Giorgi, F.: Thirty years of regional climate modeling: where are we and where
are we going next?, J. Geophys. Res.-Atmos., 124, 5696–5723, 2019.
Giorgi, F. and Bates, G. T.: The Climatological Skill of a Regional Model
over Complex Terrain, Mon. Weather Rev., 117, 2325–2347,
https://doi.org/10.1175/1520-0493(1989)117<2325:TCSOAR>2.0.CO;2, 1989.
Giorgi, F. and Mearns, L. O.: Introduction to special section: regional
climate modeling revisited, J. Geophys. Res., 104, 6335–6352, 1999.
Giorgi, F., Marinucci, M. R., and Bates, G.: Development of a second
generation regional climate model (RegCM2). I. Boundary layer and radiative
transfer processes, Mon. Weather Rev., 121, 2794–2813, 1993a.
Giorgi, F., Marinucci, M. R., Bates, G., and De Canio, G.: Development of a
second generation regional climate model (RegCM2), part II: convective
processes and assimilation of lateral boundary conditions, Mon. Weather
Rev., 121, 2814–2832, 1993b.
Giorgi, F., Francisco, R., and Pal, J. S.: Effects of a sub-gridscale
topography and landuse scheme on surface climateand hydrology. I. Effects of
temperature and water vapor disaggregation, J. Hydrometeorol., 4, 317–333,
2003.
Giorgi, F., Jones, C., and Asrar, G.: Addressing climate information needs at
the regional level: the CORDEX framework, WMO Bull., 58, 175–183, 2009.
Giorgi, F., Coppola, E., Solmon, F., Mariotti, L., Sylla, M. B., Bi, X., Elguindi, N., Diro, G. T., Nair, V., Giuliani, G., Turuncoglu, U. U., Cozzini, S., Güttler, I., O'Brien, T. A., Tawfik, A. B., Shalaby, A., Zakey, A. S., Steiner, A. L., Stordal, F., Sloan, L. C., and Brankovic, C.: RegCM4: model description and preliminary tests over multiple CORDEX domains, Clim. Res., 52, 7–29, https://doi.org/10.3354/cr01018, 2012.
Giorgi, F., Solmon, F., Xunjang, B., Coppola, E., Giuliani, G., Turunçoğlu, U., Güttler, I., Mariotti, L., Nogherotto, R., O'Brien, T. A., Tawfik, A., Elguindi, N., Piani, S., Pal, J., Tefera Diro, G., and Shalaby, A.: ictp-esp/RegCM: Paper Release, Zenodo [code], https://doi.org/10.5281/zenodo.4603556, 2021.
Grell, G. A.: Prognostic evaluation of assumptions used by cumulus
parameterizations, Mon. Weather Rev., 121, 764–787, 1993.
Grell, G. A., Dudhia J., and Stauffer, D. R.: A Description of the Fifth
Generation Penn State/NCAR Mesoscale Model (MM5),
National Center for Atmospheric Research, Boulder, CO, USA, NCAR Tech. Note, 122, NCAR/TN-398+STR 1994.
Gunn, K. L. S. and Marshall, J. S.: The distribution with size of
aggregate snowflakes, J. Meteor., 15, 452–461,
https://doi.org/10.1175/1520-0469(1958)015<0452:TDWSOA>2.0.CO;2, 1958.
Gutowski Jr., W. J., Giorgi, F., Timbal, B., Frigon, A., Jacob, D., Kang, H.-S., Raghavan, K., Lee, B., Lennard, C., Nikulin, G., O'Rourke, E., Rixen, M., Solman, S., Stephenson, T., and Tangang, F.: WCRP COordinated Regional Downscaling EXperiment (CORDEX): a diagnostic MIP for CMIP6, Geosci. Model Dev., 9, 4087–4095, https://doi.org/10.5194/gmd-9-4087-2016, 2016.
Hewitt, C. D. and Lowe, J. A.: Toward a European climate prediction system,
Bull. Amer. Meteor. Soc., 99, 1997–2001,
https://doi.org/10.1175/BAMS-D-18-0022.1, 2018.
Higgins, R. W., Kousky, V. E., and Xie, P.: Extreme Precipitation Events in the South-Central United States during May and June 2010: Historical Perspective, Role of ENSO, and Trends, J. Hydrometeorol., 12, 1056–1070, https://doi.org/10.1175/JHM-D-10-05039.1, 2011.
Holtslag, A., de Bruijn, E., and Pan, H. L.: A high resolution air mass
transformation model for short-range weather fore-casting, Mon. Weather Rev.,
118, 1561–1575, 1990.
Hong, S.-Y., Juang, H.-M. H., and Zhao, Q.: Implementation of prognostic
cloud scheme for a regional spectral model, Mon. Weather Rev., 126, 2621–2639,
1998.
Hong, S.-Y. and Lim, J.-O. J.: The WRF Single-Moment 6-Class Microphysics
Scheme (WSM6), J. Korean Meteor. Soc., 42, 129–151, 2006.
Hong, S.-Y., Dudhia, J., and Chen, S.-H.: A Revised Approach to Ice
Microphysical Processes for the Bulk Parameterization of Clouds and
Precipitation, Mon. Weather Rev., 132, 103–120, 2004.
Hostetler, S. W., Bates, G. T., and Giorgi, F.: Interactive nesting of a lake
thermal model within a regional climate model for climate change studies, J.
Geophys. Res., 98, 5045–5057, 1993.
Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F.,
Gu, G., Hong, Y., Bowman, K. P., and Stocker, E. F.: The TRMM Multisatellite
Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor
Precipitation Estimates at Fine Scales, J. Hydrometeor., 8, 38–55, https://doi.org/10.1175/JHM560.1, 2007.
International Federation of Red Cross and Red Crescent Societies (IFRC): World Disasters Report 2014: focus on culture and risk. Technical Report, International Federation of Red Cross and Red Crescent Societies, Geneva, Switzerland, 276 pp., 2014.
Joyce, R. J., Janowiak, J. E., Arkin, P. A., and Xie, P.: CMORPH: A Method
that Produces Global Precipitation Estimates from Passive Microwave and
Infrared Data at High Spatial and Temporal Resolution, J. Hydrometeor, 5,
487–503, 2004.
Kain, J. S.: The Kain–Fritsch convective parameterization: An update, J.
Appl. Meteor., 43, 170–181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2, 2004.
Kain, J. S. and Fritsch, J. M.: A one-dimensional entraining/detraining
plume model and its application in convective parameterization, J. Atmos.
Sci., 47, 2784–2802, 1990.
Kendon, E. J., Roberts, N. M., Senior, C. A., and Roberts, M. J.: Realism of
rainfall in a very high-resolution regional climate model, J. Climate, 25,
5791–5806, https://doi.org/10.1175/JCLI-D-11-00562.1, 2012.
Kendon, E. J., Ban, N., Roberts, N. M., Fowler, H. J., Roberts, M. J., Chan,
S. C., Evans, J. P., Fosser, G., and Wilkinson, J. M.: Do
convection-permitting regional climate models improve projections of future
precipitation change?, Bull. Amer. Meteor. Soc., 98, 79–93,
https://doi.org/10.1175/BAMS-D-15-0004.1, 2017.
Kessler, E.: On the Distribution and Continuity of Water Substance in
Atmospheric Circulations, in: Meteorological Monographs, Amer. Meteor. Soc., Boston, MA, 10, 84 pp., https://doi.org/10.1007/978-1-935704-36-2_1, 1969.
Khairoutdinov, M. and Kogan, Y.: A new cloud physics parameterization in a
large-eddy simulation model of marine stratocumulus, Bull. Amer. Meteorol.
Soc., 128, 229–243, 2000.
Kiehl, J., Hack, J., Bonan, G., Boville, B., Breigleb, B., Williamson, D.,
and Rasch, P.: Description of the NCAR Community Climate Model (CCM3),
National Center for Atmospheric Research, Boulder, CO, USA, NCAR Tech. Note, NCAR, 159 pp., NCAR/TN-420+STR, 1996.
Klemp, J. B. and Lilly, D. K.: Numerical simulation of hydrostatic mountain
waves, J. Atmos. Sci., 35, 78–107, 1978.
Klemp, J. B. and Dudhia, J.: An Upper Gravity-Wave Absorbing Layer for NWP
Applications, Mon. Weather Rev., 176, 3987–4004, 2008.
Lean, H. W., Clark, P. A., Dixon, M., Roberts, N. M., Fitch, A., Forbes, R.,
and Halliwell, C.: Characteristics of high-resolution versions of the Met
Office Unified Model for forecasting convection over the United Kingdom,
Mon. Weather Rev., 136, 3408–3424, https://doi.org/10.1175/2008MWR2332.1,
2008.
LeVeque, R. J.: Finite Difference Methods for Ordinary
and Partial Differential Equations, SIAM, Philadelphia, USA, https://doi.org/10.1137/1.9780898717839, 2007.
Lin, Y., Farley, R., and Orville, H.: Bulk parameterization of the snow field
in a cloud model, J. Appl. Meteor. Clim., 22, 1065–1092, 1983.
Marshall, J. S. and Palmer, W. M. K.: The distribution of raindrops with
size, J. Meteor., 5, 165–166, 1948.
Matte, D., Laprise, R., Thériault, J. M., and Lucas-Picher, P.: Spatial
spin-up of fine scales in a regional climate model simulation driven by
low-resolution boundary conditions, Clim. Dynam., 49, 563–574, https://doi.org/10.1007/s00382-016-3358-2, 2017.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S.
A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated
correlated-k model for the longwave, J. Geophys. Res., 102, 16663–16682,
1997.
Nogherotto, R., Tompkins, A. M., Giuliani, G., Coppola, E., and Giorgi, F.: Numerical framework and performance of the new multiple-phase cloud microphysics scheme in RegCM4.5: precipitation, cloud microphysics, and cloud radiative effects, Geosci. Model Dev., 9, 2533–2547, https://doi.org/10.5194/gmd-9-2533-2016, 2016.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Drewniak, B., Huang, M.,
Koven, C. D., Levis, S., Li, F., Riley, W. J., Subin, Z. M., Swenson, S. C.,
Thornton, P. E., Bozbiyik, A., Fisher, R., Kluzek, E., Lamarque, J.-F.,
Lawrence, P. J., Leung, L. R., Lipscomb, W., Muszala, S., Ricciuto, D. M.,
Sacks, W., Sun, Y., Tang, J., and Yang, Z.-L: Technical Description of
version 4.5 of the Community Land Model (CLM), National Center for Atmospheric Research, Boulder, CO, USA, NCAR Techn. Note, 422 pp., NCAR/TN-503+STR, https://doi.org/10.5065/D6RR1W7M, 2013.
Pal, J. S., Small, E., and Eltahir, E.: Simulation of regional-scale water and energy budgets: representation of subgrid cloud and precipitation processes within RegCM, J. Geophys. Res., 105, 29579–29594, 2000.
Pal, J. S., Giorgi, F., Bi, X., Elguindi, N., Solmon, F., Gao, X., Rauscher,
S. A., Francisco, R., Zakey, A., Winter, J., Ashfaq, M., Syed, F. S., Bell,
J. L., Diffenbaugh, N. S., Karmacharya, J., Konaré, A., Martinez, D., da
Rocha, R. P., Sloan, L. C., and Steiner, A. L.: The ICTP RegCM3 and RegCNET:
regional climate modeling for the developing world., Bull. Amer. Meteorol.
Soc., 88, 1395–1409, 2007.
Pichelli, E., Coppola, E., Sobolowski, S., Ban, N., Giorgi, F., Stocchi, P., Alias, A., Belušić, D., Berthou, S., Caillaud, C., Cardoso, R. M., Chan, S., Christensen, O. B., Dobler, A., de Vries, H., Goergen, K., Kendon, E. J., Keuler, K., Lenderink, G., Lorenz, T., Mishra, A. N., Panitz, H.-J., Schär, C, Soares, P. M. M., Truhetz, H., and Vergara-Temprado, J.: The first multi-model
ensemble of regional climate simulations at kilometer-scale resolution part
2: historical and future simulations of precipitation, Clim. Dynam., 56, 3581–3602, https://doi.org/10.1007/s00382-021-05657-4, 2021.
Prein, A. F. and Gobiet, A.: Impacts of uncertainties in European gridded
precipitation observations on regional climate analysis, Int. J. Climatol., 37, 305–327, https://doi.org/10.1002/joc.4706, 2017.
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K., Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S., Schmidli, J., van Lipzig, N. P. M., and Leung, R.: A review on
regional convection-permitting climate modeling: demonstrations, prospects,
and challenges, Rev. Geophys., 53, 323–361, 2015.
Ralph, F. M., Neiman, P. J., Wick, G. A., Gutman, S. I., Dettinger, M. D.,
Cayan, D. R., and White, A. B.: Flooding on California's Russian River: Role
of atmospheric rivers, Geophys. Res. Lett., 33, L13801,
https://doi.org/10.1029/2006GL026689, 2006.
Ralph, F. M., Dettinger, M. D., Cairns, M. M., Galarneau, T. J., and
Eylander, J.: Defining “atmospheric river”: How the Glossary of
Meteorology helped resolve a debate, Bull. Amer. Meteor. Soc., 99, 837–839,
https://doi.org/10.1175/BAMS-D-17-0157.1, 2018.
Rutledge, S. A. and Hobbs, P. V.: The mesoscale and microscale structure and
organization of clouds and precipitation in midlatitude cyclones. Part VIII:
A model for the “seeder-feeder” process in warm-frontal rainbands, J.
Atmos. Sci., 40, 1185–1206, 1983.
Schwartz, C. S.: Reproducing the September 2013 record-breaking rainfall
over the Colorado Front Range with high-resolution WRF forecasts, Weather
Forecast., 29, 393–402, https://doi.org/10.1175/WAF-D-13-00136.1, 2014.
Sitz, L. E., Sante, F., Farneti, R., Fuentes-Franco, R., Coppola, E., Mariotti, L., Reale, M., Sannino, G., Barreiro, M., Nogherotto, R., Giuliani, G., Graffino, G., Solidoro, C., Cossarini, G., and Giorgi, F.: Description and Evaluation of the Earth
System Regional Climate Model (RegCM–ES), J. Adv. Model. Earth Sy., 9, 1863–1886, https://doi.org/10.1002/2017MS000933, 2017.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda,
M. G., Huang, X. Y., Wang, W., and Powers, J. G.: A description of the advanced research WRF version 3,
National Center for Atmospheric Research, NCAR, Boulder, CO, USA, NCAR Techn. Note, 125 pp., NCAR/TN-475+STR, 2008.
Song, Y., Semazzi, H. M. F., Xie, L., and Ogallo, L. J.: A coupled regional
climate model for the Lake Victoria Basin of East Africa, Int. J. Climatol., 24, 57–75, 2004.
Sun, X., Xie, L., Semazzi, F., and Liu, B.: Effect of Lake Surface
Temperature on the Spatial Distribution and Intensity of the Precipitation
over the Lake Victoria Basin, Mon. Weather Rev. 143, 1179–1192, 2015.
Sundqvist, H., Berge, E., and Kristjansson, J.: Condensation and cloud
parameterization studies with a mesoscale numerical weather prediction
model, Mon. Weather Rev., 117, 1641–1657, 1989.
Talling, J. F.: The incidence of vertical mixing, and some biological and
chemical consequences, in: Tropical African lakes, Verh. Int. Ver. Limnol.,
17, 998–1012, https://doi.org/10.1080/03680770.1968.11895946, 1969.
Tiedtke, M.: A comprehensive mass flux scheme for cumulus parametrization in
large-scale models, Mon. Weather Rev., 117, 1779–1800, 1989.
Tiedtke, M.: Representation of Clouds in Large-Scale Models, Mon. Weather Rev.,
121, 3040–3061, https://doi.org/10.1175/1520-0493(1993)121<3040:ROCILS>2.0.CO;2, 1993.
Tiedtke, M.: An extension of cloud-radiation parameterization in the ECMWF
model: The representation of subgrid-scale variations of optical depth, Mon.
Weather Rev., 124, 745–750, 1996.
Tompkins, A.: Ice supersaturation in the ECMWF integrated forecast system,
Q. J. Roy. Meteor. Soc., 133, 53–63, 2007.
Tripoli, G. J. and Cotton, W. R.: A numerical investigation of several
factors contributing to the observed variable intensity of deep convection
over south Florida, J. Appl. Meteor., 19, 1037–1063, 1980.
Weisman, M. L., Davis, C., Wang, W., Manning, K. W., and Klemp, J. B.:
Experiences with 0–36-h explicit convective forecasts with the WRF-ARW
model, Weather Forecast., 23, 407–437,
https://doi.org/10.1175/2007WAF2007005.1, 2008.
Weusthoff, T., Ament, F., Arpagaus, M., and Rotach, M. W.: Assessing the
benefits of convection-permitting models by neighborhood verification:
Examples from MAP D-PHASE, Mon. Weather Rev., 138, 3418–3433, https://doi.org/10.1175/2010MWR3380.1, 2010.
Williams, P. D.: A proposed modification to the Robert–Asselin time filter,
Mon. Weather Rev., 137, 2538–2546, 2009.
Zeng, X., Zhao, M., and Dickinson, R. E.: Intercomparison of bulk aerodynamic
algorithms for the computation of sea surface fluxes using TOGA COARE and
TAO data, J. Clim., 11, 2628–2644, 1998.
Zhu, Y. and Newell, R. E.: A proposed algorithm for moisture fluxes from
atmospheric rivers, Mon. Weather Rev., 126, 725–735,
https://doi.org/10.1175/1520-0493(1998)126<0725:APAFMF>2.0.CO;2, 1998.
Short summary
In this work we describe the development of a non-hydrostatic version of the regional climate model RegCM4-NH, implemented to allow simulations at convection-permitting scales of <4 km for climate applications. The new core is described, and three case studies of intense convection are carried out to illustrate the model performances. Comparison with observations is much improved with respect to with coarse grid runs. RegCM4-NH offers a promising tool for climate investigations at a local scale.
In this work we describe the development of a non-hydrostatic version of the regional climate...