Articles | Volume 16, issue 7
https://doi.org/10.5194/gmd-16-1909-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-1909-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
06 Apr 2023
Development and technical paper |
| 06 Apr 2023
| 06 Apr 2023
Improving the representation of shallow cumulus convection with the simplified-higher-order-closure–mass-flux (SHOC+MF v1.0) approach
Maria J. Chinita
CORRESPONDING AUTHOR
Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles,
Los Angeles, California, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Mikael Witte
Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles,
Los Angeles, California, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Department of Meteorology, Naval Postgraduate School, Monterey, California, USA
Marcin J. Kurowski
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Joao Teixeira
Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles,
Los Angeles, California, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Kay Suselj
Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles,
Los Angeles, California, USA
Running Tide Technologies, Inc., Portland, Maine, USA
Georgios Matheou
Department of Mechanical Engineering, University of Connecticut, Storrs, Connecticut, USA
Peter Bogenschutz
Lawrence Livermore National Laboratory, Livermore, California, USA
Related authors
Mark A. Smalley, Mikael K. Witte, Jong-Hoon Jeong, and Maria J. Chinita
EGUsphere, https://doi.org/10.5194/egusphere-2024-1098, https://doi.org/10.5194/egusphere-2024-1098, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Evaporation of rain leads to cooler and sometimes moister surface conditions (cold pools), which can lead to further convection that alters convective, cloud, precipitation, and radiation properties. We introduce a new method of measuring cold pools, which accounts for the seasonal and daily changes in dry air turbulence in which the cold pool signatures are embedded. We then apply it to 8 years of observations in the north midlatitude Atlantic Ocean.
Peter Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
EGUsphere, https://doi.org/10.5194/egusphere-2024-839, https://doi.org/10.5194/egusphere-2024-839, 2024
Short summary
Short summary
Using a high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability of representing precipitation for these events. We find that our model is able to capture the distribution of precipitation very well, but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Mark A. Smalley, Mikael K. Witte, Jong-Hoon Jeong, and Maria J. Chinita
EGUsphere, https://doi.org/10.5194/egusphere-2024-1098, https://doi.org/10.5194/egusphere-2024-1098, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Evaporation of rain leads to cooler and sometimes moister surface conditions (cold pools), which can lead to further convection that alters convective, cloud, precipitation, and radiation properties. We introduce a new method of measuring cold pools, which accounts for the seasonal and daily changes in dry air turbulence in which the cold pool signatures are embedded. We then apply it to 8 years of observations in the north midlatitude Atlantic Ocean.
Kuo-Nung Wang, Chi O. Ao, Mary G. Morris, George A. Hajj, Marcin J. Kurowski, Francis J. Turk, and Angelyn W. Moore
Atmos. Meas. Tech., 17, 583–599, https://doi.org/10.5194/amt-17-583-2024, https://doi.org/10.5194/amt-17-583-2024, 2024
Short summary
Short summary
In this article, we described a joint retrieval approach combining two techniques, RO and MWR, to obtain high vertical resolution and solve for temperature and moisture independently. The results show that the complicated structure in the lower troposphere can be better resolved with much smaller biases, and the RO+MWR combination is the most stable scenario in our sensitivity analysis. This approach is also applied to real data (COSMIC-2/Suomi-NPP) to show the promise of joint RO+MWR retrieval.
Tim Trent, Marc Schroeder, Shu-Peng Ho, Steffen Beirle, Ralf Bennartz, Eva Borbas, Christian Borger, Helene Brogniez, Xavier Calbet, Elisa Castelli, Gilbert P. Compo, Wesley Ebisuzaki, Ulrike Falk, Frank Fell, John Forsythe, Hans Hersbach, Misako Kachi, Shinya Kobayashi, Robert E. Kursinsk, Diego Loyola, Zhengzao Luo, Johannes K. Nielsen, Enzo Papandrea, Laurence Picon, Rene Preusker, Anthony Reale, Lei Shi, Laura Slivinski, Joao Teixeira, Tom Vonder Haar, and Thomas Wagner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2808, https://doi.org/10.5194/egusphere-2023-2808, 2023
Short summary
Short summary
In a warmer future, water vapour will spend more time in the atmosphere changing global rainfall patterns. In this study, we analysed the performance of 28 water vapour records between 1988 & 2014. We find sensitivity to surface warming generally outside expected ranges, attributed to breakpoints in individual record trends & differing representations of climate variability. The implication is that longer records are required for high confidence in assessing climate trends
Matthew D. Lebsock and Mikael Witte
Atmos. Chem. Phys., 23, 14293–14305, https://doi.org/10.5194/acp-23-14293-2023, https://doi.org/10.5194/acp-23-14293-2023, 2023
Short summary
Short summary
This paper evaluates measurements of cloud drop size distributions made from airplanes. We find that as the number of cloud drops increases the distribution of the cloud drop sizes narrows. The data are used to develop a simple equation that relates the drop number to the width of the drop sizes. We then use this equation to demonstrate that existing approaches to observe the drop number from satellites contain errors that can be corrected by including the new relationship.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2023-1989, https://doi.org/10.5194/egusphere-2023-1989, 2023
Short summary
Short summary
We developed a regionally refined climate model that allows for resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3 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.
Joao Teixeira, Robert C. Wilson, and Heidar T. Thrastarson
EGUsphere, https://doi.org/10.5194/egusphere-2023-924, https://doi.org/10.5194/egusphere-2023-924, 2023
Short summary
Short summary
This paper presents direct evidence from space (solely based on observations) that CO2 increase leads to the theoretically expected effect on longwave spectral radiances. This is achieved by using a methodology that allows to isolate the CO2 effects from the temperature and water vapor effects. By searching for ensembles of temperature and water vapor profiles that are similar to each other, but have different values of CO2, it is possible to estimate the direct effects of CO2 on the spectra.
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
Geosci. Model Dev., 16, 335–352, https://doi.org/10.5194/gmd-16-335-2023, https://doi.org/10.5194/gmd-16-335-2023, 2023
Short summary
Short summary
Models that are used to simulate and predict climate often have trouble representing specific cloud types, such as stratocumulus, that are particularly thin in the vertical direction. It has been found that increasing the model resolution can help improve this problem. In this paper, we develop a novel framework that increases the horizontal and vertical resolutions only for areas of the globe that contain stratocumulus, hence reducing the model runtime while providing better results.
Kevin M. Smalley, Matthew D. Lebsock, Ryan Eastman, Mark Smalley, and Mikael K. Witte
Atmos. Chem. Phys., 22, 8197–8219, https://doi.org/10.5194/acp-22-8197-2022, https://doi.org/10.5194/acp-22-8197-2022, 2022
Short summary
Short summary
We use geostationary satellite observations to track pockets of open-cell (POC) stratocumulus and analyze how precipitation, cloud microphysics, and the environment change. Precipitation becomes more intense, corresponding to increasing effective radius and decreasing number concentrations, while the environment remains relatively unchanged. This implies that changes in cloud microphysics are more important than the environment to POC development.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
Short summary
Short summary
An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 15, 117–129, https://doi.org/10.5194/amt-15-117-2022, https://doi.org/10.5194/amt-15-117-2022, 2022
Short summary
Short summary
Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that
smears2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is
towardsor
away fromthe Sun, so calculating
across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.
Siraput Jongaramrungruang, Georgios Matheou, Andrew K. Thorpe, Zhao-Cheng Zeng, and Christian Frankenberg
Atmos. Meas. Tech., 14, 7999–8017, https://doi.org/10.5194/amt-14-7999-2021, https://doi.org/10.5194/amt-14-7999-2021, 2021
Short summary
Short summary
This study shows how precision error and bias in column methane retrieval change with different instrument specifications and the impact of spectrally complex surface albedos on retrievals. We show how surface interferences can be mitigated with an optimal spectral resolution and a higher polynomial degree in a retrieval process. The findings can inform future satellite instrument designs to have robust observations capable of separating real CH4 plume enhancements from surface interferences.
Richard J. Roy, Matthew Lebsock, and Marcin J. Kurowski
Atmos. Meas. Tech., 14, 6443–6468, https://doi.org/10.5194/amt-14-6443-2021, https://doi.org/10.5194/amt-14-6443-2021, 2021
Short summary
Short summary
This study describes the potential capabilities of a hypothetical spaceborne radar to observe water vapor within clouds.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021, https://doi.org/10.5194/amt-14-5555-2021, 2021
Short summary
Short summary
Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
Zhibo Zhang, Qianqian Song, David B. Mechem, Vincent E. Larson, Jian Wang, Yangang Liu, Mikael K. Witte, Xiquan Dong, and Peng Wu
Atmos. Chem. Phys., 21, 3103–3121, https://doi.org/10.5194/acp-21-3103-2021, https://doi.org/10.5194/acp-21-3103-2021, 2021
Short summary
Short summary
This study investigates the small-scale variations and covariations of cloud microphysical properties, namely, cloud liquid water content and cloud droplet number concentration, in marine boundary layer clouds based on in situ observation from the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign. We discuss the dependence of cloud variations on vertical location in cloud and the implications for warm-rain simulations in the global climate models.
Peter A. Bogenschutz, Shuaiqi Tang, Peter M. Caldwell, Shaocheng Xie, Wuyin Lin, and Yao-Sheng Chen
Geosci. Model Dev., 13, 4443–4458, https://doi.org/10.5194/gmd-13-4443-2020, https://doi.org/10.5194/gmd-13-4443-2020, 2020
Short summary
Short summary
This paper documents a tool that has been developed that can be used to accelerate the development and understanding of climate models. This version of the model, known as a the single-column model, is much faster to run than the full climate model, and we demonstrate that this tool can be used to quickly exploit model biases that arise due to physical processes. We show examples of how this single-column model can directly benefit the field.
Siraput Jongaramrungruang, Christian Frankenberg, Georgios Matheou, Andrew K. Thorpe, David R. Thompson, Le Kuai, and Riley M. Duren
Atmos. Meas. Tech., 12, 6667–6681, https://doi.org/10.5194/amt-12-6667-2019, https://doi.org/10.5194/amt-12-6667-2019, 2019
Short summary
Short summary
This paper demonstrates the use of high-resolution 2-D plume imagery from airborne remote sensing retrievals to quantify methane point-source emissions. It shows significant improvements on the flux estimates without the need for direct wind speed measurements. This paves the way for enhanced flux estimates in future field campaign and space-based observations to better understand the magnitude and distribution of various point sources of methane.
Christoph Heinze, Veronika Eyring, Pierre Friedlingstein, Colin Jones, Yves Balkanski, William Collins, Thierry Fichefet, Shuang Gao, Alex Hall, Detelina Ivanova, Wolfgang Knorr, Reto Knutti, Alexander Löw, Michael Ponater, Martin G. Schultz, Michael Schulz, Pier Siebesma, Joao Teixeira, George Tselioudis, and Martin Vancoppenolle
Earth Syst. Dynam., 10, 379–452, https://doi.org/10.5194/esd-10-379-2019, https://doi.org/10.5194/esd-10-379-2019, 2019
Short summary
Short summary
Earth system models for producing climate projections under given forcings include additional processes and feedbacks that traditional physical climate models do not consider. We present an overview of climate feedbacks for key Earth system components and discuss the evaluation of these feedbacks. The target group for this article includes generalists with a background in natural sciences and an interest in climate change as well as experts working in interdisciplinary climate research.
Luis F. Millán, Matthew D. Lebsock, and Joao Teixeira
Atmos. Chem. Phys., 19, 8491–8502, https://doi.org/10.5194/acp-19-8491-2019, https://doi.org/10.5194/acp-19-8491-2019, 2019
Short summary
Short summary
The synergy of the collocated Advanced Microwave Scanning Radiometer (AMSR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global estimates of marine boundary layer water vapor. AMSR provides the total column water vapor, while MODIS provides the water vapor above the cloud layers. The difference between the two gives the vapor between the surface and the cloud top, which may be interpreted as the boundary layer water vapor.
Dejian Fu, Susan S. Kulawik, Kazuyuki Miyazaki, Kevin W. Bowman, John R. Worden, Annmarie Eldering, Nathaniel J. Livesey, Joao Teixeira, Fredrick W. Irion, Robert L. Herman, Gregory B. Osterman, Xiong Liu, Pieternel F. Levelt, Anne M. Thompson, and Ming Luo
Atmos. Meas. Tech., 11, 5587–5605, https://doi.org/10.5194/amt-11-5587-2018, https://doi.org/10.5194/amt-11-5587-2018, 2018
Jesse Dorrestijn, Brian H. Kahn, João Teixeira, and Fredrick W. Irion
Atmos. Meas. Tech., 11, 2717–2733, https://doi.org/10.5194/amt-11-2717-2018, https://doi.org/10.5194/amt-11-2717-2018, 2018
Short summary
Short summary
Atmospheric Infrared Sounder (AIRS) satellite observations are used to quantify the scale-dependent variance of temperature and water vapor in the atmosphere. The scale dependence is much more variable than previously thought, using a new methodology based on individual satellite swaths. A break in the scale dependence is found to vary from less than 100 to greater than 1000 km. These new variance scaling results are of high importance for improving climate GCM subgrid parameterizations.
Peter A. Bogenschutz, Andrew Gettelman, Cecile Hannay, Vincent E. Larson, Richard B. Neale, Cheryl Craig, and Chih-Chieh Chen
Geosci. Model Dev., 11, 235–255, https://doi.org/10.5194/gmd-11-235-2018, https://doi.org/10.5194/gmd-11-235-2018, 2018
Short summary
Short summary
This paper compares results of developmental versions of a widely used climate model. The simulations only differ in the choice of how to model the sub-grid-scale physics in the atmospheric model. This work is novel because it is the first time that a particular physics option has been tested in a fully coupled climate model. Here, we demonstrate that this physics option has the ability to produce credible coupled climate simulations, with improved metrics in certain fields.
Brian H. Kahn, Georgios Matheou, Qing Yue, Thomas Fauchez, Eric J. Fetzer, Matthew Lebsock, João Martins, Mathias M. Schreier, Kentaroh Suzuki, and João Teixeira
Atmos. Chem. Phys., 17, 9451–9468, https://doi.org/10.5194/acp-17-9451-2017, https://doi.org/10.5194/acp-17-9451-2017, 2017
Short summary
Short summary
The global-scale patterns of subtropical marine boundary layer clouds are investigated with coincident NASA A-train satellite and reanalysis data. This study is novel in that all data are used at the finest spatial and temporal resolution possible. Our results are consistent with surface-based data and suggest that the combination of satellite and reanalysis data sets have potential to add to the global context of our understanding of the subtropical cumulus-dominated marine boundary layer.
K. Thayer-Calder, A. Gettelman, C. Craig, S. Goldhaber, P. A. Bogenschutz, C.-C. Chen, H. Morrison, J. Höft, E. Raut, B. M. Griffin, J. K. Weber, V. E. Larson, M. C. Wyant, M. Wang, Z. Guo, and S. J. Ghan
Geosci. Model Dev., 8, 3801–3821, https://doi.org/10.5194/gmd-8-3801-2015, https://doi.org/10.5194/gmd-8-3801-2015, 2015
Short summary
Short summary
This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that is implemented in CAM v5.3. We show mean climate and tropical variability results from global simulations. The model has a degradation in precipitation skill but improvements in shortwave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. We also show estimation of computational expense and sensitivity to number of subcolumns.
M. K. Witte, P. Y. Chuang, and G. Feingold
Atmos. Chem. Phys., 14, 6729–6738, https://doi.org/10.5194/acp-14-6729-2014, https://doi.org/10.5194/acp-14-6729-2014, 2014
Related subject area
Atmospheric sciences
Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations
A dynamic approach to three-dimensional radiative transfer in subkilometer-scale numerical weather prediction models: the dynamic TenStream solver v1.0
Evaluation and development of surface layer scheme representation of temperature inversions over boreal forests in Arctic wintertime conditions
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
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
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
The ddeq Python library for point source quantification from remote sensing images (Version 1.0)
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
Investigating Ground-Level Ozone Pollution in Semi-Arid and Arid Regions of Arizona Using WRF-Chem v4.4 Modeling
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
FUME 2.0 – Flexible Universal processor for Modeling Emissions
Assessment of tropospheric ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Application of regional meteorology and air quality models based on MIPS CPU Platform
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024, https://doi.org/10.5194/gmd-17-3321-2024, 2024
Short summary
Short summary
Any interpretation of climate model data requires a comprehensive evaluation of the model performance. Numerous error metrics exist for this purpose, and each focuses on a specific aspect of the relationship between reference and model data. Thus, a comprehensive evaluation demands the use of multiple error metrics. However, this can lead to confusion. We propose a clustering technique to reduce the number of error metrics needed and a composite error metric to simplify the interpretation.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
Short summary
Short summary
Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
Short summary
Short summary
Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Nathan Patrick Arnold
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-245, https://doi.org/10.5194/gmd-2023-245, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Earth System Models often represent the land surface at smaller scales than the atmosphere, but surface-atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
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
Short summary
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
Short summary
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.
Cited articles
Beljaars, A., Balsamo, G., Bechtold, P., Bozzo, A., Forbes, R., Hogan, R.
J., Köhler, M., Morcrette, J. J., Tompkins, A. M., Viterbo, P., and
Wedi, N.: The Numerics of Physical Parametrization in the ECMWF Model,
Front. Earth Sci., 6, 1–18, https://doi.org/10.3389/feart.2018.00137, 2018.
Betts, A. K.: Non-precipitating cumulus convection and its parameterization,
Q. J. Roy. Meteor. Soc., 99, 178–196,
https://doi.org/10.1002/qj.49709941915, 1973.
Blackadar, A. K.: The vertical distribution of wind and turbulent exchange
in a neutral atmosphere, J. Geophys. Res., 67, 3095–3102, 1962.
Bogenschutz, P. A. and Krueger, S. K.: A simplified PDF parameterization of
subgrid-scale clouds and turbulence for cloud-resolving models, J. Adv.
Model. Earth Sy., 5, 195–211, https://doi.org/10.1002/jame.20018, 2013.
Bogenschutz, P. A., Tang, S., Caldwell, P. M., Xie, S., Lin, W., and Chen, Y.-S.: The E3SM version 1 single-column model, Geosci. Model Dev., 13, 4443–4458, https://doi.org/10.5194/gmd-13-4443-2020, 2020.
Böing, S. J., Jonker, H. J. J., Siebesma, A. P., and Grabowski, W. W.:
Influence of the subcloud layer on the development of a deep convective
ensemble, J. Atmos. Sci., 69, 2682–2698,
https://doi.org/10.1175/JAS-D-11-0317.1, 2012.
Brient, F., Couvreux, F., Villefranque, N., Rio, C., and Honnert, R.:
Object-Oriented Identification of Coherent Structures in Large Eddy
Simulations: Importance of Downdrafts in Stratocumulus, Geophys. Res. Lett.,
46, 2854–2864, https://doi.org/10.1029/2018GL081499, 2019.
Brown, A. R., Cederwall, R. T., Chlond, A., Duynkerke, P. G., Golaz, J. C.,
Khairoutdinov, M., Lewellen, D. C., Lock, A. P., MacVean, M. K., Moeng, C.
H., Neggers, R. A. J., Siebesma, A. P., and Stevens, B.: Large-eddy
simulation of the diurnal cycle of shallow cumulus convection over land, Q. J. Roy. Meteor. Soc., 128, 1075–1093,
https://doi.org/10.1256/003590002320373210, 2002.
Caldwell, P. M., Terai, C. R., Hillman, B., Keen, N. D., Bogenschutz, P.,
Lin, W., Beydoun, H., Taylor, M., Bertagna, L., Bradley, A. M., Clevenger,
T. C., Donahue, A. S., Eldred, C., Foucar, J., Golaz, J. C., Guba, O.,
Jacob, R., Johnson, J., Krishna, J., Liu, W., Pressel, K., Salinger, A. G.,
Singh, B., Steyer, A., Ullrich, P., Wu, D., Yuan, X., Shpund, J., Ma, H. Y.,
and Zender, C. S.: Convection-Permitting Simulations With the E3SM Global
Atmosphere Model, J. Adv. Model. Earth Sy., 13, e2021MS002544,
https://doi.org/10.1029/2021MS002544, 2021.
Cheng, A. and Xu, K. M.: Simulation of shallow cumuli and their transition
to deep convective clouds by cloud-resolving models with different
third-order turbulence closures, Q. J. Roy. Meteor. Soc., 132, 359–382,
https://doi.org/10.1256/qj.05.29, 2006.
Cheng, A. and Xu, K. M.: Simulation of boundary-layer cumulus and
stratocumulus clouds using a cloud-resolving model with low- and third-order
turbulence closures, J. Meteorol. Soc. Japan, 86A, 67–86,
https://doi.org/10.2151/jmsj.86A.67, 2008.
Chinita, M.: Code for SHOC+MF_v1.0, Zenodo [code], https://doi.org/10.5281/zenodo.7011628, 2022a.
Chinita, M.: Data for SHOC+MF_v1.0, Zenodo [data set], https://doi.org/10.5281/zenodo.7011652, 2022b.
Chinita, M. J., Matheou, G., and Teixeira, J.: A joint probability
density-based decomposition of turbulence in the atmospheric boundary layer,
Mon. Weather Rev., 146, 503–523, https://doi.org/10.1175/MWR-D-17-0166.1, 2018.
Chinita, M. J., Matheou, G., and Miranda, P. M. A.: Large-eddy simulation of
very stable boundary layers. Part I: Modeling methodology, Q. J. Roy. Meteor. Soc., 148, 1805–1823, https://doi.org/10.1002/qj.4279,
2022a.
Chinita, M. J., Matheou, G., and Miranda, P. M. A.: Large-eddy simulation of
very stable boundary layers. Part II: Length scales and anisotropy in
stratified atmospheric turbulence, Q. J. Roy. Meteor. Soc., 148, 1824–1839,
https://doi.org/10.1002/qj.4280, 2022b.
Chung, D. and Matheou, G.: Large-eddy simulation of stratified turbulence.
Part I: A vortex-based subgrid-scale model, J. Atmos. Sci., 71, 1863–1879,
https://doi.org/10.1175/JAS-D-13-0126.1, 2014.
Chung, D., Matheou, G., and Teixeira, J.: Steady-state large-eddy
simulations to study the stratocumulus to shallow cumulus cloud transition,
J. Atmos. Sci., 69, 3264–3276, https://doi.org/10.1175/JAS-D-11-0256.1,
2012.
Cohen, Y., Lopez-Gomez, I., Jaruga, A., He, J., Kaul, C. M., and Schneider,
T.: Unified Entrainment and Detrainment Closures for Extended
Eddy-Diffusivity Mass-Flux Schemes, J. Adv. Model. Earth Sy., 12,
e2020MS002162, https://doi.org/10.1029/2020MS002162, 2020.
Couvreux, F., Hourdin, F., and Rio, C.: Resolved versus parametrized
boundary-layer plumes. Part I: A parametrization-oriented conditional
sampling in large-eddy simulations, Bound.-Lay. Meteorol., 134, 441–458,
https://doi.org/10.1007/s10546-009-9456-5, 2010.
Couvreux, F., Bazile, E., Rodier, Q., Maronga, B., Matheou, G., Chinita, M.
J., Edwards, J., van Stratum, B. J. H., van Heerwaarden, C. C., Huang, J.,
Moene, A. F., Cheng, A., Fuka, V., Basu, S., Bou-Zeid, E., Canut, G., and
Vignon, E.: Intercomparison of Large-Eddy Simulations of the Antarctic
Boundary Layer for Very Stable Stratification, Bound.-Lay. Meteorol.,
176, 369–400, https://doi.org/10.1007/s10546-020-00539-4, 2020.
Deardorff, J. W.: The Counter-Gradient Heat Flux in the Lower Atmosphere and
in the Laboratory, J. Atmos. Sci., 23, 503–506, https://doi.org/10.1175/1520-0469(1966)023<0503:tcghfi>2.0.co;2, 1966.
E3SM Project, DOE: Energy Exascale Earth System Model v2.0. (Computer Software), DOE [software], https://doi.org/10.11578/E3SM/dc.20210927.1, 2021.
Firl, G. J. and Randall, D. A.: Fitting and analyzing les using multiple
trivariate Gaussians, J. Atmos. Sci., 72, 1094–1116,
https://doi.org/10.1175/JAS-D-14-0192.1, 2015.
Fitch, A. C.: An improved double-Gaussian closure for the subgrid vertical
velocity probability distribution function, J. Atmos. Sci., 76, 285–304,
https://doi.org/10.1175/JAS-D-18-0149.1, 2019.
Golaz, J. C., Larson, V. E., and Cotton, W. R.: A PDF-based model for
boundary layer clouds. Part I: Method and model description, J. Atmos. Sci.,
59, 3540–3551, https://doi.org/10.1175/1520-0469(2002)059<3540:APBMFB>2.0.CO;2, 2002.
Golaz, J. C., Caldwell, P. M., Van Roekel, L. P., Petersen, M. R., Tang, Q.,
Wolfe, J. D., Abeshu, G., Anantharaj, V., Asay-Davis, X. S., Bader, D. C.,
Baldwin, S. A., Bisht, G., Bogenschutz, P. A., Branstetter, M., Brunke, M.
A., Brus, S. R., Burrows, S. M., Cameron-Smith, P. J., Donahue, A. S.,
Deakin, M., Easter, R. C., Evans, K. J., Feng, Y., Flanner, M., Foucar, J.
G., Fyke, J. G., Griffin, B. M., Hannay, C., Harrop, B. E., Hoffman, M. J.,
Hunke, E. C., Jacob, R. L., Jacobsen, D. W., Jeffery, N., Jones, P. W.,
Keen, N. D., Klein, S. A., Larson, V. E., Leung, L. R., Li, H. Y., Lin, W.,
Lipscomb, W. H., Ma, P. L., Mahajan, S., Maltrud, M. E., Mametjanov, A.,
McClean, J. L., McCoy, R. B., Neale, R. B., Price, S. F., Qian, Y., Rasch,
P. J., Reeves Eyre, J. E. J., Riley, W. J., Ringler, T. D., Roberts, A. F.,
Roesler, E. L., Salinger, A. G., Shaheen, Z., Shi, X., Singh, B., Tang, J.,
Taylor, M. A., Thornton, P. E., Turner, A. K., Veneziani, M., Wan, H., Wang,
H., Wang, S., Williams, D. N., Wolfram, P. J., Worley, P. H., Xie, S., Yang,
Y., Yoon, J. H., Zelinka, M. D., Zender, C. S., Zeng, X., Zhang, C., Zhang,
K., Zhang, Y., Zheng, X., Zhou, T., and Zhu, Q.: The DOE E3SM Coupled Model
Version 1: Overview and Evaluation at Standard Resolution, J. Adv. Model. Earth Sy., 11, 2089–2129, https://doi.org/10.1029/2018MS001603, 2019.
Han, J. and Bretherton, C. S.: TKE-based moist eddy-diffusivity mass-flux
(EDMF) parameterization for vertical turbulent mixing, Weather Forecast.,
34, 869–886, https://doi.org/10.1175/WAF-D-18-0146.1, 2019.
Han, J. and Pan, H. L.: Revision of convection and vertical diffusion
schemes in the NCEP Global Forecast System, Weather Forecast., 26, 520–533,
https://doi.org/10.1175/WAF-D-10-05038.1, 2011.
Han, J., Witek, M. L., Teixeira, J., Sun, R., Pan, H. L., Fletcher, J. K.,
and Bretherton, C. S.: Implementation in the NCEP GFS of a hybrid
eddy-diffusivity mass-flux (EDMF) boundary layer parameterization with
dissipative heating and modified stable boundary layer mixing, Weather
Forecast., 31, 341–352, https://doi.org/10.1175/WAF-D-15-0053.1, 2016.
Holtslag, A. A. M. and Boville, B. A.: Local versus nonlocal boundary-layer
diffusion in a global climate model, J. Climate, 6, 1825–1842,
https://doi.org/10.1175/1520-0442(1993)006<1825:LVNBLD>2.0.CO;2, 1993.
Holtslag, A. A. M. and Moeng, C.-H.: Eddy diffusivity and countergradient
transport in the convective atmospheric boundary layer, J. Atmos. Sci., 48, 1690–1698,
https://doi.org/10.1175/1520-0469(1991)048<1690:EDACTI>2.0.CO;2, 1991.
Kohler, M., Ahlgrimm, M., and Beljaars, A.: Unified treatment of dry
convective and stratocumulus-topped boundary layers in the ECMWF model, Q. J. Roy. Meteor. Soc., 137, 43–57, https://doi.org/10.1002/qj.713, 2011.
Kurowski, M. J., Suselj, K., and Grabowski, W. W.: Is Shallow Convection
Sensitive to Environmental Heterogeneities?, Geophys. Res. Lett., 46,
1785–1793, https://doi.org/10.1029/2018GL080847, 2019a.
Kurowski, M. J., Thrastarson, H. T., Suselj, K., and Teixeira, J.: Towards
unifying the planetary boundary layer and shallow convection in CAM5 with
the eddy-diffusivity/mass-flux approach, Atmosphere, 10, 484,
https://doi.org/10.3390/atmos10090484, 2019b.
Lamaakel, O. and Matheou, G.: Galilean invariance of shallow cumulus
convection large-eddy simulations, J. Comput. Phys., 427, 110012,
https://doi.org/10.1016/j.jcp.2020.110012, 2021.
Matheou, G.: Turbulence Structure in a Stratocumulus Cloud, Atmosphere, 9, 392,
https://doi.org/10.3390/atmos9100392, 2018.
Matheou, G. and Chung, D.: Large-eddy simulation of stratified turbulence.
Part II: Application of the stretched-vortex model to the atmospheric
boundary layer, J. Atmos. Sci., 71, 4439–4460,
https://doi.org/10.1175/JAS-D-13-0306.1, 2014.
Matheou, G. and Teixeira, J.: Sensitivity to physical and numerical aspects
of large-eddy simulation of stratocumulus, Mon. Weather Rev., 147,
2621–2639, https://doi.org/10.1175/MWR-D-18-0294.1, 2019.
Matheou, G., Chung, D., and Teixeira, J.: On the synergy between numerics
and subgrid scale modeling in LES of stratified flows: Grid convergence of a
stratocumulus-topped boundary layer., in: Eighth Int. Symp. on Stratified Flows, Vol. 1, San Diego,
CA, NASA Jet Propulsion Laboratory, http://hdl.handle.net/2014/46171 (last access: 20 March 2023), 2016.
Morinishi, Y., Lund, T. S., Vasilyev, O. V, and Moin, P.: Fully Conservative
Higher Order Finite Difference Schemes for Incompressible Flow, J. Comput.
Phys., 143, 90–124, https://doi.org/10.1006/jcph.1998.5962,
1998.
Neggers, R. A. J.: A dual mass flux framework for boundary layer convection.
Part II: Clouds, J. Atmos. Sci., 66, 1489–1506,
https://doi.org/10.1175/2008JAS2636.1, 2009.
Olson, J. B., Kenyon, J. S., Angevine, W. A., Brown, J. M., Pagowski, M.,
and Sušelj, K.: A Description of the MYNN-EDMF Scheme and the Coupling
to Other Components in WRF–ARW, NOAA Technical Memorandum OAR GSD-61,
https://doi.org/10.25923/n9wm-be49, 2019.
Richtmyer, R. and Morton, K.: Difference methods for initial value
problems, 2nd edn., Wiley-Interscience, New York, 405 pp., 1967.
Rio, C. and Hourdin, F.: A thermal plume model for the convective boundary
layer: Representation of cumulus clouds, J. Atmos. Sci., 65, 407–425,
https://doi.org/10.1175/2007JAS2256.1, 2008.
Romps, D. M. and Kuang, Z.: Nature versus nurture in shallow convection, J.
Atmos. Sci., 67, 1655–1666, https://doi.org/10.1175/2009JAS3307.1, 2010.
Schneider, T., Teixeira, J., Bretherton, C. S., Brient, F., Pressel, K. G.,
Schär, C., and Siebesma, A. P.: Climate goals and computing the future
of clouds, Nat. Clim. Change, 7, 3–5, https://doi.org/10.1038/nclimate3190,
2017.
Sherwood, S. C., Bony, S., and Dufresne, J. L.: Spread in model climate
sensitivity traced to atmospheric convective mixing, Nature, 505, 37–42,
https://doi.org/10.1038/nature12829, 2014.
Siebesma, A., Bretherton, C. S., Brown, A., Chlond, A., Cuxart, J.,
Duynkerke, P. G., Jiang, H., Khairoutdinov, M., Lewellen, D., Moeng, C. H.,
Sanchez, E., Stevens, B., and Stevens, D. E.: A large eddy simulation
intercomparison study of shallow cumulus convection, J. Atmos. Sci., 60,
1201–1219, https://doi.org/10.1175/1520-0469(2003)60<1201:ALESIS>2.0.CO;2, 2003.
Siebesma, A. P. and Cuijpers, J. W. M.: Evaluation of parametric assumptions
for shallow cumulus convection, J. Atmos. Sci., 52, 650–666,
https://doi.org/10.1175/1520-0469(1995)052<0650:EOPAFS>2.0.CO;2, 1995.
Siebesma, A. P., Soares, P. M. M., and Teixeira, J.: A combined
eddy-diffusivity mass-flux approach for the convective boundary layer, J.
Atmos. Sci., 64, 1230–1248, https://doi.org/10.1175/JAS3888.1, 2007.
Siebesma, P. and Teixeira, J.: An advection-diffusion scheme for the
convective boundary layer: Description and 1D-results, in: Proc. 14th Symp. on Boundary Layers and Turbulence, Aspen, CO,
Amer. Meteor. Soc., 133–136, 2000.
Soares, P. M. M., Miranda, P. M. A., Siebesma, A. P., and Teixeira, J.: An
eddy-diffusivity/mass-flux parametrization for dry and shallow cumulus
convection, Q. J. Roy. Meteor. Soc., 130, 3365–3383,
https://doi.org/10.1256/qj.03.223, 2004.
Stevens, B.: Quasi-steady analysis of a PBL model with an Eddy-diffusivity
profile and nonlocal fluxes, Mon. Weather Rev., 128, 824–836,
https://doi.org/10.1175/1520-0493(2000)128<0824:QSAOAP>2.0.CO;2, 2000.
Suselj, K., Teixeira, J., and Chung, D.: A unified model for moist
convective boundary layers based on a stochastic eddy-diffusivity/mass-flux
parameterization, J. Atmos. Sci., 70, 1929–1953,
https://doi.org/10.1175/JAS-D-12-0106.1, 2013.
Suselj, K., Hogan, T. F., and Teixeira, J.: Implementation of a stochastic
eddy-diffusivity/mass-flux parameterization into the Navy Global
environmental model, Weather Forecast., 29, 1374–1390,
https://doi.org/10.1175/WAF-D-14-00043.1, 2014.
Suselj, K., Kurowski, M. J., and Teixeira, J.: A unified
eddy-diffusivity/mass-flux approach for modeling atmospheric convection, J.
Atmos. Sci., 76, 2505–2537, https://doi.org/10.1175/JAS-D-18-0239.1, 2019a.
Suselj, K., Kurowski, M. J., and Teixeira, J.: On the factors controlling
the development of shallow convection in eddy-diffusivity/mass-flux models,
J. Atmos. Sci., 76, 433–456, https://doi.org/10.1175/JAS-D-18-0121.1,
2019b.
Suselj, K., Teixeira, J., Kurowski, M. J., and Molod, A.: Improving the
representation of subtropical boundary layer clouds in the NASA GEOS model
with the eddy-diffusivity/mass-flux parameterization, Mon. Weather Rev.,
149, 793–809, https://doi.org/10.1175/MWR-D-20-0183.1, 2021.
Takahashi, H., Luo, Z. J., and Stephens, G.: Revisiting the Entrainment
Relationship of Convective Plumes: A Perspective From Global Observations,
Geophys. Res. Lett., 48, e2020GL092349, https://doi.org/10.1029/2020GL092349, 2021.
Tan, Z., Kaul, C. M., Pressel, K. G., Cohen, Y., Schneider, T., and
Teixeira, J.: An Extended Eddy-Diffusivity Mass-Flux Scheme for Unified
Representation of Subgrid-Scale Turbulence and Convection, J. Adv. Model. Earth Sy., 10, 770–800,
https://doi.org/10.1002/2017MS001162, 2018.
Teixeira, J. and Cheinet, S.: A simple mixing length formulation for the
eddy-diffusivity parameterization of dry convection, Bound.-Lay. Meteorol., 110, 435–453,
https://doi.org/10.1023/B:BOUN.0000007230.96303.0d, 2004.
Teixeira, J. and Siebesma, P.: A mass flux/K-diffusion approach to the
parameterization of the convective boundary layer: Global model results,
in: Proc. 14th Symp. on Boundary Layers and Turbulence, Aspen, CO,
Amer. Meteor. Soc., 231–234, 2000.
Teixeira, J., Ferreira, J. P., Miranda, P. M. A., Haack, T., Doyle, J.,
Siebsema, A. P., and Salgado, R.: A new mixing-length formulation for the
parameterization of dry convection: Implementation and evaluation in
mesoscale model, Mon. Weather Rev., 132, 2698–2707,
https://doi.org/10.1175/MWR2808.1, 2004.
Teixeira, J., Stevens, B., Bretherton, C. S., Cederwall, R., Doyle, J. D.,
Golaz, J. C., Holtslag, A. A. M., Klein, S. A., Lundquist, J. K., Randall,
D. A., Siebesma, A. P., and Soares, P. M. M.: Parameterization of the
atmospheric boundary layer: A view from just above the inversion, B. Am.
Meteorol. Soc., 89, 453–458, https://doi.org/10.1175/BAMS-89-4-453, 2008.
Tiedtke, M.: A Comprehensive Mass Flux Scheme for Cumulus Parameterization
in Large-Scale Models, Mon. Weather Rev., 117, 1779–1800, 1989.
Witek, M. L., Teixeira, J., and Matheou, G.: An Integrated TKE-based eddy
diffusivity/mass flux boundary layer closure for the dry convective boundary
layer, J. Atmos. Sci., 68, 1526–1540,
https://doi.org/10.1175/2011JAS3548.1, 2011.
Witte, M. K., Herrington, A., Teixeira, J., Kurowski, M., Chinita, M. J.,
Storer, R. L., Suselj, K., Matheou, G., and Bacmeister, J.: Augmenting the
double-Gaussian representation of atmospheric turbulence and convection via
a coupled stochastic multi-plume mass flux scheme, Mon. Weather Rev., 150, 2339–2355,
https://doi.org/10.1175/MWR-D-21-0215.1, 2022.
Wu, E., Yang, H., Kleissl, J., Suselj, K., Kurowski, M. J., and Teixeira,
J.: On the parameterization of convective downdrafts for marine
stratocumulus clouds, Mon. Weather Rev., 148, 1931–1950,
https://doi.org/10.1175/MWR-D-19-0292.1, 2020.
Yoshimura, H., Mizuta, R., and Murakami, H.: A spectral cumulus
parameterization scheme interpolating between two convective updrafts with
semi-lagrangian calculation of transport by compensatory subsidence, Mon.
Weather Rev., 143, 597–621, https://doi.org/10.1175/MWR-D-14-00068.1, 2015.
Short summary
Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper,...
