Articles | Volume 10, issue 3
https://doi.org/10.5194/gmd-10-1363-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-1363-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model experiment description paper
| 
31 Mar 2017
Model experiment description paper |
| 31 Mar 2017
Global 7 km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7): experimental design and preliminary results
Japan Agency for Marine-Earth Science and Technology, 3173-25
Showa-machi, Kanazawa-ku, Yokohama, Kanagawa 236-0001, Japan
Akiyoshi Wada
Meteorological Research Institute, Japan Meteorological Agency, 1-1
Nagamine, Tsukuba, Ibaraki 305-0052, Japan
Masahiro Sawada
Meteorological Research Institute, Japan Meteorological Agency, 1-1
Nagamine, Tsukuba, Ibaraki 305-0052, Japan
Hiromasa Yoshimura
Meteorological Research Institute, Japan Meteorological Agency, 1-1
Nagamine, Tsukuba, Ibaraki 305-0052, Japan
Ryo Onishi
Japan Agency for Marine-Earth Science and Technology, 3173-25
Showa-machi, Kanazawa-ku, Yokohama, Kanagawa 236-0001, Japan
Shintaro Kawahara
Japan Agency for Marine-Earth Science and Technology, 3173-25
Showa-machi, Kanazawa-ku, Yokohama, Kanagawa 236-0001, Japan
Wataru Sasaki
Japan Agency for Marine-Earth Science and Technology, 3173-25
Showa-machi, Kanazawa-ku, Yokohama, Kanagawa 236-0001, Japan
Tomoe Nasuno
Japan Agency for Marine-Earth Science and Technology, 3173-25
Showa-machi, Kanazawa-ku, Yokohama, Kanagawa 236-0001, Japan
Munehiko Yamaguchi
Meteorological Research Institute, Japan Meteorological Agency, 1-1
Nagamine, Tsukuba, Ibaraki 305-0052, Japan
Takeshi Iriguchi
Meteorological Research Institute, Japan Meteorological Agency, 1-1
Nagamine, Tsukuba, Ibaraki 305-0052, Japan
Masato Sugi
Meteorological Research Institute, Japan Meteorological Agency, 1-1
Nagamine, Tsukuba, Ibaraki 305-0052, Japan
Yoshiaki Takeuchi
Meteorological Research Institute, Japan Meteorological Agency, 1-1
Nagamine, Tsukuba, Ibaraki 305-0052, Japan
Related authors
Chihiro Kodama, Tomoki Ohno, Tatsuya Seiki, Hisashi Yashiro, Akira T. Noda, Masuo Nakano, Yohei Yamada, Woosub Roh, Masaki Satoh, Tomoko Nitta, Daisuke Goto, Hiroaki Miura, Tomoe Nasuno, Tomoki Miyakawa, Ying-Wen Chen, and Masato Sugi
Geosci. Model Dev., 14, 795–820, https://doi.org/10.5194/gmd-14-795-2021, https://doi.org/10.5194/gmd-14-795-2021, 2021
Short summary
Short summary
This paper describes the latest stable version of NICAM, a global atmospheric model, developed for high-resolution climate simulations toward the IPCC Assessment Report. Our model explicitly treats convection, clouds, and precipitation and could reduce the uncertainty of climate change projection. A series of test simulations demonstrated improvements (e.g., high cloud) and issues (e.g., low cloud, precipitation pattern), suggesting further necessity for model improvement and higher resolutions.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
Short summary
Short summary
JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Hiromasa Yoshimura
Geosci. Model Dev., 15, 2561–2597, https://doi.org/10.5194/gmd-15-2561-2022, https://doi.org/10.5194/gmd-15-2561-2022, 2022
Short summary
Short summary
This paper proposes a new double Fourier series (DFS) method on a sphere that improves the numerical stability of a model compared with conventional DFS methods. The shallow-water model and the advection model using the new DFS method give stable results without the appearance of high-wavenumber noise near the poles. The model using the new DFS method is faster than the model using spherical harmonics (especially at high resolutions) and gives almost the same results.
Chihiro Kodama, Tomoki Ohno, Tatsuya Seiki, Hisashi Yashiro, Akira T. Noda, Masuo Nakano, Yohei Yamada, Woosub Roh, Masaki Satoh, Tomoko Nitta, Daisuke Goto, Hiroaki Miura, Tomoe Nasuno, Tomoki Miyakawa, Ying-Wen Chen, and Masato Sugi
Geosci. Model Dev., 14, 795–820, https://doi.org/10.5194/gmd-14-795-2021, https://doi.org/10.5194/gmd-14-795-2021, 2021
Short summary
Short summary
This paper describes the latest stable version of NICAM, a global atmospheric model, developed for high-resolution climate simulations toward the IPCC Assessment Report. Our model explicitly treats convection, clouds, and precipitation and could reduce the uncertainty of climate change projection. A series of test simulations demonstrated improvements (e.g., high cloud) and issues (e.g., low cloud, precipitation pattern), suggesting further necessity for model improvement and higher resolutions.
Hideaki Kawai, Seiji Yukimoto, Tsuyoshi Koshiro, Naga Oshima, Taichu Tanaka, Hiromasa Yoshimura, and Ryoji Nagasawa
Geosci. Model Dev., 12, 2875–2897, https://doi.org/10.5194/gmd-12-2875-2019, https://doi.org/10.5194/gmd-12-2875-2019, 2019
Short summary
Short summary
The representation of clouds was significantly improved in the climate model MRI-ESM2. The model is planned for use in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) simulations. In particular, a notorious lack of reflection of solar radiation over the Southern Ocean was drastically improved in the model. The score of the spatial pattern of radiative fluxes for MRI-ESM2 is better than for any CMIP5 model. We present modifications implemented in the various physics schemes.
Keigo Matsuda and Ryo Onishi
Atmos. Chem. Phys., 19, 1785–1799, https://doi.org/10.5194/acp-19-1785-2019, https://doi.org/10.5194/acp-19-1785-2019, 2019
Short summary
Short summary
This paper presents a parameterization to predict the influence of microscale turbulent clustering of cloud droplets on the radar reflectivity factor, based on a direct numerical simulation (DNS) of turbulence. The proposed parameterization takes account of the turbulent clustering structure of droplets with arbitrary size distributions. This paper also discusses quantitative influences on realistic radar observations, applying the parameterization to high-resolution cloud-simulation data.
Yuichi Kunishima and Ryo Onishi
Atmos. Chem. Phys., 18, 16619–16630, https://doi.org/10.5194/acp-18-16619-2018, https://doi.org/10.5194/acp-18-16619-2018, 2018
Short summary
Short summary
This paper shows the tracking simulation of motions and growth of the entire cloud particles, including aerosols and rain drops, in vertically developing clouds. A cutting-edge direct simulation code (i.e., the Lagrangian cloud simulator) has been run for an extremely vertically elongated three-dimensional domain, with 1 cm in width and 3 km in depth. This unique domain makes the computation-demanding simulation feasible and has led to the success of the present full tracking simulation.
Kunihiko Kodera, Nawo Eguchi, Hitoshi Mukougawa, Tomoe Nasuno, and Toshihiko Hirooka
Atmos. Chem. Phys., 17, 615–625, https://doi.org/10.5194/acp-17-615-2017, https://doi.org/10.5194/acp-17-615-2017, 2017
Short summary
Short summary
An exceptional strengthening of the middle atmospheric subtropical jet occurred without an apparent relationship with the tropospheric circulation. The analysis of this event demonstrated downward penetration of stratospheric influence to the troposphere: in the north polar region amplification of planetary wave occurred due to a deflection by the strong middle atmospheric subtropical jet, whereas in the tropics, increased tropopause temperature suppressed equatorial convective activity.
Ryo Onishi and Axel Seifert
Atmos. Chem. Phys., 16, 12441–12455, https://doi.org/10.5194/acp-16-12441-2016, https://doi.org/10.5194/acp-16-12441-2016, 2016
Short summary
Short summary
This study includes massively parallel simulation results on droplet collisions in turbulence. The attained maximum Taylor-microscale-based Reynolds number (Re) exceeds 103, which steps into the typical range (O(103)–O(104)) of observed Re in turbulent clouds. The results clearly show that the Re dependence of turbulence enhancement on droplet collision growth is relevant for cloud microphysics modeling. This will promote the discussion on the Re dependence of turbulent collision statistics.
Axel Seifert and Ryo Onishi
Atmos. Chem. Phys., 16, 12127–12141, https://doi.org/10.5194/acp-16-12127-2016, https://doi.org/10.5194/acp-16-12127-2016, 2016
Short summary
Short summary
In this study we investigate the effect of turbulence on rain formation in shallow clouds. Several formulations of the collision kernel for turbulent flows using different turbulence models have been suggested in recent years. Here we compare two formulations and find that, although both give a significant increase in collision rate, the differences are quite large, especially for high Reynolds numbers as they are observed in clouds.
N. Eguchi, K. Kodera, and T. Nasuno
Atmos. Chem. Phys., 15, 297–304, https://doi.org/10.5194/acp-15-297-2015, https://doi.org/10.5194/acp-15-297-2015, 2015
Short summary
Short summary
The dynamical coupling process between stratosphere and troposphere in the tropical tropopause layer (TTL) during stratospheric sudden warming (SSW) was investigated using simulation data of global non-hydrostatic model (NICAM) that does not use cumulus parameterization. The results suggested that increased stratospheric tropical upwelling associated with SSW induced decreased static stability in TTL, which contributes to increased convective activity and changes in its large-scale organizations
Related subject area
Atmospheric sciences
WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
RoadSurf 1.1: open-source road weather model library
Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States
The ddeq Python library for point source quantification from remote sensing images (version 1.0)
Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
A general comprehensive evaluation method for cross-scale precipitation forecasts
Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
An improved and extended parameterization of the CO2 15 µm cooling in the middle and upper atmosphere (CO2_cool_fort-1.0)
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)
Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms
Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling
An objective identification technique for potential vorticity structures associated with African easterly waves
Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2
Assessment of surface ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4
Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta)
FUME 2.0 – Flexible Universal processor for Modeling Emissions
DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties
Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent
Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands
Balloon drift estimation and improved position estimates for radiosondes
Emission ensemble approach to improve the development of multi-scale emission inventories
What is the relative impact of nudging and online coupling on meteorological variables, pollutant concentrations and aerosol optical properties?
Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Assessing acetone for the GISS ModelE2.1 Earth system model
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
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote sensing observations
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
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
Short summary
Short summary
Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
Short summary
Short summary
Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
Short summary
Short summary
Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
Short summary
Short summary
Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
Short summary
Short summary
RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
Short summary
Short summary
The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 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.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
Short summary
Short summary
The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
Short summary
Short summary
By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
Short summary
Short summary
We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
Short summary
Short summary
This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
Short summary
Short summary
Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
Short summary
Short summary
The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
Short summary
Short summary
The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
Short summary
Short summary
There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
Short summary
Short summary
This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and 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.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
Short summary
Short summary
This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
Short summary
Short summary
We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
Short summary
Short summary
This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
Short summary
Short summary
Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
Short summary
Short summary
In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
Short summary
Short summary
We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 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 for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
Short summary
Short summary
Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
Short summary
Short summary
This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
Short summary
Short summary
HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev., 17, 3783–3799, https://doi.org/10.5194/gmd-17-3783-2024, https://doi.org/10.5194/gmd-17-3783-2024, 2024
Short summary
Short summary
This paper presents a method for calculating balloon drift from historical radiosonde ascent data. The drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes but would also work for dropsondes, ozonesondes, or any other in situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
Short summary
Short summary
An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev., 17, 3645–3665, https://doi.org/10.5194/gmd-17-3645-2024, https://doi.org/10.5194/gmd-17-3645-2024, 2024
Short summary
Short summary
This study is about the modelling of the atmospheric composition in Europe during the summer of 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impacts of two modelling processes that are able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Shuai Wang, Mengyuan Zhang, Yueqi Gao, Peng Wang, Qingyan Fu, and Hongliang Zhang
Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024, https://doi.org/10.5194/gmd-17-3617-2024, 2024
Short summary
Short summary
Numerical models are widely used in air pollution modeling but suffer from significant biases. The machine learning model designed in this study shows high efficiency in identifying such biases. Meteorology (relative humidity and cloud cover), chemical composition (secondary organic components and dust aerosols), and emission sources (residential activities) are diagnosed as the main drivers of bias in modeling PM2.5, a typical air pollutant. The results will help to improve numerical models.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
Short summary
Short summary
Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024, https://doi.org/10.5194/gmd-17-3487-2024, 2024
Short summary
Short summary
This paper describes and evaluates an improvement to the representation of acetone in the GISS ModelE2.1 Earth system model. We simulate acetone's concentration and transport across the atmosphere as well as its dependence on chemistry, the ocean, and various global emissions. Comparisons of our model’s estimates to past modeling studies and field measurements have shown encouraging results. Ultimately, this paper contributes to a broader understanding of acetone's role in the atmosphere.
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.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
EGUsphere, https://doi.org/10.22541/essoar.169903618.82717612/v2, https://doi.org/10.22541/essoar.169903618.82717612/v2, 2024
Short summary
Short summary
Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate of the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
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.
Cited articles
Baba, Y., Takahashi, K., Sugimura, T., and Goto, K.: Dynamical core of an atmospheric general circulation model on a yin–yang grid, Mon. Weather Rev., 138, 3988–4005, https://doi.org/10.1175/2010MWR3375.1, 2010.
Bénard, P., Vivoda, J., Mašek, J., Smolíková, P., Yessad, K., Smith, Ch., Brožková, R., and Geleyn, J.-F.: Dynamical kernel of the Aladin-NH spectral limited-area model: Revised formulation and sensitivity experiments, Q. J. Roy. Meteor. Soc., 136, 155–169, https://doi.org/10.1002/qj.522, 2010.
Bernardet, L., Tallapragada, V., Bao, S., Trahan, S., Kwon, Y., Liu, Q., Tong, M., Biswas, M., Brown, T., Stark, D., Carson, L., Yablonsky, R., Uhlhorn, E., Gopalakrishnan, S., Zhang, X., Marchok, T., Kuo, B., and Gall, R.: Community support and transition of research to operations for the hurricane weather research and Forecasting model, B. Am. Meteorol. Soc., 96, 953–960, https://doi.org/10.1175/BAMS-D-13-00093.1, 2015.
Braun, S. A. and Tao, W.-K.: Sensitivity of high-resolution simulations of Hurricane Bob (1991) to planetary boundary layer parameterizations, Mon. Weather Rev., 128, 3941–3961, 2000.
Bubnová, R., Hello, G., Bénard, P., and Geleyn, J.-F.: Integration of the fully elastic equations cast in the hydrostatic pressure terrain-following coordinate in the framework of the ARPEGE/Aladin NWP system, Mon. Weather Rev., 123, 515–535, 1995.
Carr III, L. E. and Elsberry, R. L.: Dynamical tropical cyclone track forecast errors, Part I: Tropical region error sources, Weather Forecast., 15, 641–661, https://doi.org/10.1175/1520-0434(2000)015<0641:DTCTFE>2.0.CO;2, 2000.
Cheong, H.-B.: Application of double Fourier series to the shallow-water equations on a sphere, J. Comput. Phys., 165, 261–287, 2000.
Choi, Y., Kida, S., and Takahashi, K.: The impact of oceanic circulation and phase transfer on the dispersion of radionuclides released from the Fukushima Dai-ichi Nuclear Power Plant, Biogeosciences, 10, 4911–4925, https://doi.org/10.5194/bg-10-4911-2013, 2013.
Fairall, C. W., Bradley, E. F., Rogers, D. P., Edson, J. B., and Young, G. S.: Bulk parameterization of air-sea fluxes for Tropical Ocean-Global Atmosphere Coupled-Ocean Atmosphere Response Experiment, J. Geophys. Res., 101, 747–764, 1996.
Fairall, C. W., Bradley, E. F., Hare, J. E., Grachev, A. A., and Edson, J. B.: Bulk parameterization of air-sea fluxes: updates and verification for the COARE algorithm, J. Climate, 16, 571–591, 2003.
Fierro, A. O., Rogers, R. F., Marks, F. D., and Nolan, D. S.: The impact of horizontal grid spacing on the microphysical and kinematic structures of strong tropical cyclones simulated with the WRF-ARW model, Mon. Weather Rev., 137, 3717–3743, https://doi.org/10.1175/2009MWR2946.1, 2009.
Fudeyasu, H., Wang, Y., Satoh, M., Nasuno, T., Miura, H., and Yanase, W.: Global cloud-system-resolving model NICAM successfully simulated the lifecycles of two real tropical cyclones, Geophys. Res. Lett., 35, L22808, https://doi.org/10.1029/2008GL036003, 2008.
Fudeyasu, H., Wang, Y., Satoh, M., Nasuno, T., Miura, H., and Yanase, W.: Multiscale interactions in the life cycle of a tropical cyclone simulated in a global cloud-system-resolving model, Part I: Large-scale and storm-scale evolutions, Mon. Weather Rev., 138, 4285–4304, https://doi.org/10.1175/2010MWR3474.1, 2010a.
Fudeyasu, H., Wang, Y., Satoh, M., Nasuno, T., Miura, H., and Yanase, W.: Multiscale interactions in the life cycle of a tropical cyclone simulated in a global cloud-system-resolving model, Part II: System-scale and mesoscale processes, Mon. Weather Rev., 138, 4305–4327, https://doi.org/10.1175/2010MWR3475.1, 2010b.
Gentry, M. S. and Lackmann, G. M.: Sensitivity of simulated tropical cyclone structure and intensity to horizontal resolution, Mon. Weather Rev., 138, 688–704, https://doi.org/10.1175/2009MWR2976.1, 2010.
Goerss, J. S.: Tropical cyclone track forecasts using an ensemble of dynamical models, Mon. Weather Rev., 128, 1187–1193, https://doi.org/10.1175/1520-0493(2000)128<1187:TCTFUA>2.0.CO;2, 2000.
Gravel, S. and Staniforth, A.: A mass-conserving semi-Lagraingian scheme for the shallow-water equations, Mon. Weather Rev., 122, 243–248, 1994.
Hasumi, H.: CCSR Ocean Component model (COCO) version 4.0. CCSR Rep 25, The University of Tokyo, Chiba, Japan, 2006.
Hortal, M.: The development and testing of a new two-time-level semi-Lagrangian scheme (SETTLS) in the ECMWF forecast model, Q. J. Roy. Meteor. Soc., 128, 1671–1687, https://doi.org/10.1002/qj.200212858314, 2002.
Ito, K., Kuroda, T., Saito, K., and Wada, A.: Forecasting a large number of tropical cyclone intensities around Japan using a high-resolution atmosphere–ocean coupled model, Weather Forecast., 30, 793–808, https://doi.org/10.1175/WAF-D-14-00034.1, 2015.
Japan Meteorological Agency (JMA): Outline of the operational numerical weather prediction at the Japan Meteorological Agency, Appendix to WMO technical progress report on the global data-processing and forecasting system and numerical weather prediction, 188 pp., available at: http://www.jma.go.jp/jma/jma-eng/jma-center/nwp/outline2013-nwp/index.htm, 2013.
Japan Meteorological Agency: Annual report on the activities of the RSMC Tokyo-typhoon center, 90 pp., available at: http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/AnnualReport/2014/Text/Text2014.pdf, 2014.
Japan Meteorological Agency: The upgrade history of the global spectral model, available at: http://www.wis-jma.go.jp/ddb/latest_modelupgrade.txt, 2016.
Joint Typhoon Warning Center: 2008 Annual tropical cyclone report, 116 pp., available at: http://www.usno.navy.mil/NOOC/nmfc-ph/RSS/jtwc/atcr/2008atcr.pdf, 2008.
Kageyama, A. and Sato, T.: The Yin-Yang grid: An overset grid in spherical geometry, Geochem. Geophys. Geosyst., 5, Q09005, https://doi.org/10.1029/2004GC000734, 2004.
Kajikawa, Y., Miyamoto, Y., Yoshida, R., Yamaura, T., Yashiro, H., and Tomita, H.: Resolution dependence of deep convections in a global simulation from over 10-kilometer to sub-kilometer grid spacing, Prog. Earth Planet. Sci., 3, 16, https://doi.org/10.1186/s40645-016-0094-5, 2016.
Kanada, S. and Wada, A.: Numerical study on the extremely rapid intensification of an intense tropical cyclone, Typhoon Ida (1958), J. Atmos. Sci., 72, 4194–4217, https://doi.org/10.2151/jmsj.2015-037, 2015.
Kawahara, S.: Volume Data Visualizer for Google Earth™ (VDVGE), http://www.jamstec.go.jp/ceist/aeird/avcrg/vdvge.en.html, (accessed 27 April 2016), 2012.
Kawahara, S., Onishi, R., Goto, K., and Takahashi, K.: Realistic representation of clouds in Google Earth, Proc. SIGGRAPH Asia 2015 VHPC, https://doi.org/10.1145/2818517.2818541, 2015.
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K, Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and Takahashi, K.: The JRA-55 reanalysis: General specifications and basic characteristics, J. Meteor. Soc. Jpn., 93, 5–48, https://doi.org/10.2151/jmsj.2015-001, 2015.
Kodama, C., Yamada, Y., Noda, A. T., Kikuchi, K., Kajikawa, Y., Nasuno, T., Tomita, T., Yamaura, T., Takahashi, T. G., Hara, M., Kawatani, Y., Satoh, M., and Sugi, M.: A 20-year climatology of a NICAM AMIP-type simulation, J. Meteor. Soc. Jpn., 93, 393–424, https://doi.org/10.2151/jmsj.2015-024, 2015.
Kurihara, Y., Sakurai, T., and Kuragano, T.: Global daily sea surface temperature analysis using data from satellite microwave radiometer, satellite infrared radiometer and in-situ observations, Weather Bull., 73, s1–s18, 2006 (in Japanese).
Louis, J. F.: A parametric model of vertical eddy fluxes in the atmosphere, Bound.-Lay. Meteor., 2, 187–202, 1979.
Louis, J. F., Tiedtke, M., and Geleyn, J. F.: A short history of the operational PBL parameterization at ECMWF, Proc. Workshop on Planetary Boundary Layer Parameterization, Reading, UK, ECMWF, 59–79, 1982.
Lu, L.-F., Onishi, R., and Takahashi, K.: The effect of wind on long-term summer water temperature trends in Tokyo Bay, Japan, Ocean Dynam., 65, 919–930, https://doi.org/10.1007/s10236-015-0848-4, 2015.
Madden, R. A. and Julian, P. R.: Description of global-scale circulation cells in the tropics with a 40–50 day period, J. Atmos. Sci., 29, 1109–1123, 1972.
Matsueda, M. and Endo, H.: Verification of medium-range MJO forecasts with TIGGE, Geophys. Res. Lett., 38, L11801, https://doi.org/10.1029/2011GL047480, 2011.
Mellor, G. L. and Yamada, T.: A hierarchy of turbulence closure models for planetary boundary layers, J. Atmos. Sci., 31, 1791–1806, 1974.
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for geophysical fluid problems, Rev. Geophys. Space Phys., 20, 851–875, 1982.
Miller, M. J., Palmer, T. N., and Swinbank, R.: Parameterization and influence of subgridscale orography in general circulation and numerical weather prediction models, Meteor. Atmos. Phys., 40, 84–109, 1989.
Miura, H., Satoh, M., Tomita H., Noda, A. T., Nasuno, T., and Iga, S.: A short-duration global cloud-resolving simulation with a realistic land and sea distribution, Geophys. Res. Lett., 34, L02804, https://doi.org/10.1029/2006GL027448, 2007a.
Miura, H., Satoh, M., Nasuno T., Noda, A. T., and Oouchi, K.: A Madden-Julian oscillation event realistically simulated by a global cloud-resolving model, Science, 318, 1763–1765, https://doi.org/10.1126/science.1148443, 2007b.
Miyakawa, T., Satoh, M., Miura, H., Tomita, H., Yashiro, H., Noda, A. T., Yamada, Y., Kodama, C., Kimoto, M., and Yoneyama, K.: Madden-Julian oscillation prediction skill of a new-generation global model demonstrated using a supercomputer, Nat. Comm., 5, 3769, https://doi.org/10.1038/ncomms4769, 2014.
Miyamoto, K.: Introduction of the reduced Gaussian grid into the operational global NWP model at JMA, CAS/JSC WGNE Research Activities in Atmospheric and Ocean Modelling, 36, 6.9–6.10, 2006.
Miyamoto, Y., Kajikawa, Y., Yoshida, R., Yamaura, T., Yashiro, H., and Tomita, H.: Deep moist atmospheric convection in a subkilometer global simulation, Geophys. Res. Lett., 40, 4922–4926, https://doi.org/10.1002/grl.50944, 2013.
Miyamoto, Y., Yoshida, R., Yamaura, T., Yashiro, H., Tomita, H., and Kajikawa, Y.: Does convection vary in different cloud disturbances?, Atmos. Sci. Lett., 16, 305–309, https://doi.org/10.1002/asl2.558, 2015.
Miyoshi, T., Kondo, K., and Terasaki, K.: Big ensemble data assimilation in numerical weather prediction, Computer, 48, 15–21, https://doi.org/10.1109/MC.2015.332, 2015.
Mizuta, R., Oouchi, K., Yoshimura, H., Noda, A., Katayama, K., Yukimoto, S., Hosaka, M., Kusunoki, S., Kawai, H., and Nakagawa, M.: 20-km-mesh global climate simulations using JMA-GSM model – mean climate states, J. Meteor. Soc. Jpn., 84, 165–185, https://doi.org/10.2151/jmsj.84.165, 2006.
Moon, I.-J., Ginis, I., Hara, T., and Thomas, B.: A physics-based parameterization of air–sea momentum flux at high wind speeds and its impact on hurricane intensity predictions, Mon. Weather Rev., 135, 2869–2878, https://doi.org/10.1175/MWR3432.1, 2007.
Murakami, H. and Sugi, M.: Effect of model resolution on tropical cyclone climate projections, SOLA, 6, 73–76, https://doi.org/10.2151/sola.2010-019, 2010.
Murakami, H., Mizuta, R., and Shindo, E.: Future changes in tropical cyclone activity projected by multi-physics and multi-SST ensemble experiments using the 60-km-mesh MRI-AGCM, Clim. Dynam., 39, 2569–2584, https://doi.org/10.1007/s00382-011-1223-x, 2012a.
Murakami, H., Wang, Y., Yoshimura, H., Mizuta, R., Sugi, M., Shindo, E., Adachi, Y., Yukimoto, S., Hosaka, M., Kusunoki, S., Ose, T., and Kitoh, A.: Future changes in tropical cyclone activity projected by the new high-resolution MRI-AGCM, J. Climate, 25, 3237–3260, https://doi.org/10.1175/JCLI-D-11-00415.1, 2012b.
Nakanishi, M. and Niino, H.: An improved Mellor-Yamada level-3 model with condensation physics: Its design and verification, Bound.-Lay. Meteor., 112, 1–31, 2004.
Nakanishi, M. and Niino, H.: Development of an Improved Turbulence Closure Model for the Atmospheric Boundary Layer, J. Meteor. Soc. Jpn., 87, 895–912, https://doi.org/10.2151/jmsj.87.895, 2009.
Nakano, M., Nasuno, T., Sawada, M., and Satoh, M.: Intraseasonal variability and tropical cyclogenesis in the western North Pacific simulated by a global nonhydrostatic atmospheric model, Geophys. Res. Lett., 42, 565–571, https://doi.org/10.1002/2014GL062479, 2015.
Nasuno, T.: Forecast skill of Madden–Julian oscillation events in a global nonhydrostatic model during the CINDY2011/DYNAMO observation period, SOLA, 9, 69–73, https://doi.org/10.2151/sola.2013-016, 2013.
Nasuno, T., Yamada, H., Nakano, M., Kubota, H., Sawada, M., and Yoshida, R.: Global cloud-permitting simulations of Typhoon Fengshen (2008), Geosci. Lett., 3, 32, https://doi.org/10.1186/s40562-016-0064-1, 2016.
Noda, A. T., Oouchi, K., Satoh, M., Tomita, H., Iga, S.-I., and Tsushima, Y.: Importance of the subgrid-scale turbulent moist process: Cloud distribution in global cloud-resolving simulations, Atmos Res., 96, 208–217, https://doi.org/10.1016/j.atmosres.2009.05.007, 2010.
Okamoto, K., Aonashi, K., Kubota, T., and Tashima, T.: Experimental assimilation of the GPM-Core DPR reflectivity profiles for Typhoon Halong (2014), Mon. Weather Rev., 144, 2307–2326, https://doi.org/10.1175/MWR-D-15-0399.1, 2016.
Onishi, R. and Takahashi, K.: A warm-bin–cold-bulk hybrid cloud microphysical model, J. Atmos. Sci., 69, 1474–1497, https://doi.org/10.1175/JAS-D-11-0166.1, 2012.
Onishi, R., Takahashi, K., and Komori, S.: High-resolution simulations for turbulent clouds developing over the ocean, in: Gas Transfer at Water Surfaces, edited by: Komori, S., McGillis, W., and Kurose, R., Kyoto University Press, 6, 582–592, 2011.
Onogi, K., Tsutsui, J., Koide, H., Sakamoto, M., Kobayashi, S., Hatsushika, H., Matsumoto, T., Yamazaki, N., Kamahori, H., Takahashi, K., Kadokura, S., Wada, K., Kato, K., Oyama, R., Ose, T., Mannoji, N., and Taira, R.: The JRA-25 Reanalysis, J. Meteor. Soc. Jpn., 85, 369-432, https://doi.org/10.2151/jmsj.85.369, 2007.
Oouchi, K., Noda, A. T., Satoh, M., Miura, H., Tomita, H., Nasuno, T., and Iga, S.: A simulated preconditioning of typhoon genesis controlled by a boreal summer Madden-Julian Oscillation event in a global cloud-resolving mode, SOLA, 5, 65–68, https://doi.org/10.2151/sola.2009-017, 2009.
Priestley, A.: A quasi-conservative version of the semi-Lagrangian advection scheme, Mon. Weather Rev., 121, 621–629, 1993.
Randall, D. and Pan, D.-M.: Implementation of the Arakawa-Schubert cumulus parameterization with a prognostic closure, The representation of cumulus convection in numerical models, AMS Meteor. Monogr. Series, 46, 137–144, 1993.
Randall, D., Khairoutdinov, M., Arakawa, A., and Grabowski, W.: Breaking the cloud parameterization deadlock, B. Am. Meteorol. Soc., 84, 1547–1564, https://doi.org/10.1175/BAMS-84-11-1547, 2003.
Rogers, R. F., Reasor, P., and Lorsolo, S.: Airborne doppler observations of the inner-core structural differences between intensifying and steady-state tropical cyclones, Mon. Weather Rev., 141, 2970–2991, https://doi.org/10.1175/MWR-D-12-00357.1, 2013.
Sasaki, W., Onishi, R., Fuchigami, H., Goto, K., Nishikawa, S., Ishikawa, Y., and Takahashi, K.: MJO simulation in a cloud-system-resolving global ocean-atmosphere coupled model, Geophys. Res. Lett., 43, 9352–9360, https://doi.org/10.1002/2016GL070550, 2016.
Satoh, M., Matsuno, T., Tomita, H., Miura, H., Nasuno, T., and Iga, S.: Nonhydrostatic icosahedral atmospheric model (NICAM) for global cloud resolving simulations, J. Comput. Phys., 227, 3486–3514, https://doi.org/10.1016/j.jcp.2007.02.006, 2008.
Satoh, M., Tomita, H., Yashiro, H., Miura, H, Kodama, C., Seiki, T., Noda, A. T., Yamada, Y., Goto, D., Sawada, M., Miyoshi, T., Niwa, Y., Hara, M., Ohno, T., Iga, S., Arakawa, T., Inoue, T., and Kubokawa, H.: The non-hydrostatic icosahedral atmospheric model: description and development, Prog. Earth Planet. Sci., 1, 18, https://doi.org/10.1186/s40645-014-0018-1, 2014.
Sekiguchi, M. and Nakajima, T.: A k-distribution-based radiation code and its computational optimization for an atmospheric general circulation model, J. Quant. Spectrosc. Ra., 109, 2779–2793, https://doi.org/10.1016/j.jqsrt.2008.07.013, 2008.
Shibata, K., Yoshimura, H., Ohizumi, M., Hosaka, M., and Sugi, M.: A simulation of troposphere, stratosphere and mesosphere with MRI/JMA98 GCM, Pap. Meteor. Geophys., 50, 15–53, 1999.
Shapiro, L. J. and Willoughby, H. E.: The response of balanced hurricanes to local sources of heat and momentum, J. Atmos. Sci., 39, 378–394, 1982.
Smith, R. N. B.: A scheme for predicting layer clouds and their water content in a general circulation model, Q. J. Roy. Meteor. Soc., 116, 435–460, 1990.
Takahashi, K., Peng, X., Ohnishi, R., Sugimura, T., Ohdaira, M., Goto, K., and Fuchigami, H.: Multi-scale weather/climate simulations with Multi-Scale Simulator for the Geoenvironment (MSSG) on the Earth Simulator, Ann. Rep. Earth Simulator Center, April 2006–March 2007, 27–33, ISSN 1348–5822, 2006.
Takahashi, K., Onishi, R., Baba, Y., Kida, S., Matsuda, K., Goto, K., and Fuchigami, H.: Challenge toward the prediction of typhoon behaviour and down pour, J. Phys. Conference Series, 454, 012072, 2013.
Takata, K., Emori, S., and Watanabe, T.: Development of the minimal advanced treatments of surface interaction and runoff, Global Planet. Change, 38, 209–222, 2003.
Taniguchi, H., Yanase, W., and Satoh, M.: Ensemble simulation of cyclone Nargis by a global cloud-system-resolving model—modulation of cyclogenesis by the Madden-Julian oscillation, J. Meteor. Soc. Jpn., 88, 571–591, https://doi.org/10.2151/jmsj.2010-317, 2010.
Tomita, H.: New microphysical schemes with five and six categories by diagnostic generation of cloud ice, J. Meteorol. Soc. Jpn., 86, 121–142, https://doi.org/10.2151/jmsj.86A.121, 2008.
Tomita, H., Tsugawa, M., Satoh, M., and Goto, K.: Shallow water model on a modified icosahedral geodesic grid by using spring dynamics, J. Comp. Phys., 174, 579–613, https://doi.org/10.1006/jcph.2001.6897, 2001.
Toro, E. F.: A weighted average flux method for hyperbolic conservation laws, P. R. Soc. London, 423, 401–418, 1989.
Wang, B. and Rui, H.: Synoptic climatology of transient tropical intraseasonal convection anomalies: 1975–1985, Meteorol. Atmos. Phys., 44, 43–61, 1990.
Wang, B. and Xie, X.: A model for the boreal summer intraseasonal oscillation, J. Atmos. Sci., 54, 72–86, 1997.
Wang, H. and Wang, Y.: A numerical study of typhoon Megi (2010): Part I: Rapid intensification, Mon. Weather Rev., 142, 29–48, https://doi.org/10.1175/MWR-D-13-00070.1, 2014.
Wedi, N. P. and Smolarkiewicz, P. K.: A framework for testing global non-hydrostatic models, Q. J. Roy. Meteor. Soc., 135, 469–484, https://doi.org/10.1002/qj.377, 2009.
Wicker, L. J. and Skamarock, W. C.: Time-split-ting methods for elastic models using forward time schemes, Mon. Weather Rev., 130, 2088–2097, 2002.
Xiang, B., Lin, S.-J., Zhao, M., Zhang, S., Vecchi, G., Li, T., Jiang, X., Harris, L., and Chen, J.-H.: Beyond weather time-scale prediction for hurricane Sandy and super typhoon Haiyan in a global climate model, Mon. Weather Rev., 143, 524–535, https://doi.org/10.1175/MWR-D-14-00227.1, 2015.
Yablonsky, R. M. and Ginis, I.: Limitation of one-dimensional ocean models for coupled hurricane–ocean model forecasts, Mon. Weather Rev., 137, 4410–4419, https://doi.org/10.1175/2009MWR2863.1, 2009.
Yabu, S.: Development of longwave radiation scheme with consideration of scattering by clouds in JMA global model, CAS/JSC WGNE Research Activities in Atmospheric and Oceanic Modelling, 43, 4.07–4.08, 2013.
Yamada, H., Nasuno, T., Yanase, W., and Satoh, M.: Role of the vertical structure of a simulated tropical cyclone in its motion: A case study of Typhoon Fengshen (2008), SOLA, 12, 203–208, https://doi.org/10.2151/sola.2016-041, 2016.
Yamaguchi, M., Iriguchi, T., Nakazawa, T., and Wu, C.-C.: An observing system experiment for Typhoon Conson (2004) using a singular vector method and DOTSTAR data, Mon. Weather Rev., 137, 2801–2816, 2009.
Yamaguchi, M., Nakazawa, T., and Hoshino, S.: On the relative benefits of a multi-centre grand ensemble for tropical cyclone track prediction in the western North Pacific, Q. J. Roy. Meteor. Soc., 138, 2019–2029, https://doi.org/10.1002/qj.1937, 2012.
Yamaguchi, M., Vitart, F., Lang, S. T. K., Magnusson, L., Elsberry, R. L., Elliott, G., Kyouda, M., and Nakazawa, T.: Global distribution on the skill of tropical cyclone activity forecasts from short- to medium-range time scales, Weather Forecast., 30, 1695–1709, https://doi.org/10.1175/WAF-D-14-00136.1, 2015.
Yanase, W., Taniguchi, H., and Satoh, M.: The genesis of tropical cyclone Nargis (2008): Environmental modulation and numerical predictability, J. Meteor. Soc. Jpn., 88, 497–519, https://doi.org/10.2151/jmsj.2010-314, 2010.
Yoshimura, H.: Development of a nonhydrostatic global spectral atmospheric model using double Fourier series, CAS/JSC WGNE Research Activities in Atmospheric and Ocean Modeling, 42, 3.05–3.06, 2012.
Yoshimura, H. and Matsumura, T.: A Semi-Lagrangian scheme conservative in the vertical direction, CAS/JSC WGNE Research Activities in Atmospheric and Ocean Modeling, 33, 3.19–3.20, 2003.
Yoshimura, H. and Matsumura, T.: A two-time-level vertically-conservative semi-Lagrangian semi-implicit double Fourier series AGCM, CAS/JSC WGNE Research Activities in Atmospheric and Ocean Modeling, 35, 3.25–3.26, 2005.
Yukimoto, S. and Coauthors: Meteorological Research Institute-Earth System Model Version 1 (MRI-ESM1) – Model Description, Technical Reports of the Meteorological Research Institute, No. 64, 2011.
Zarzycki, C. M.: Tropical cyclone intensity errors associated with lack of two-way ocean coupling in high-resolution global simulations, J. Climate, 29, 8589–8610, https://doi.org/10.1175/JCLI-D-16-0273.1, 2016.
Zhang, D. and Anthes, R. A.: A high-resolution model of the planetary boundary layer–sensitivity tests and comparisons with SESAME-79 Data, J. Appl. Meteor., 21, 1594–1609, 1982.
Zhang, F., Minamide, M., and Clothiaux, E. E.: Potential impacts of assimilating all-sky infrared satellite radiances from GOES-R on convection-permitting analysis and prediction of tropical cyclones, Geophys. Res. Lett., 43, 2954–2963, https://doi.org/10.1002/2016GL068468, 2016.
Short summary
Three 7 km mesh next-generation global models and a 20 km mesh conventional global model were run to improve tropical cyclone (TC) prediction. The 7 km mesh models reduce systematic errors in the TC track, intensity and wind radii predictions. However, the simulated TC structures and their intensities in each case are very different for each model. These results suggest that the development of more sophisticated initialization techniques and model physics is needed to further improvement.
Three 7 km mesh next-generation global models and a 20 km mesh conventional global model were...
