Articles | Volume 8, issue 6
https://doi.org/10.5194/gmd-8-1677-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-8-1677-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
09 Jun 2015
Model description paper |
| 09 Jun 2015
libcloudph++ 1.0: a single-moment bulk, double-moment bulk, and particle-based warm-rain microphysics library in C++
Institute of Geophysics, Faculty of Physics, University of Warsaw, Warsaw, Poland
A. Jaruga
Institute of Geophysics, Faculty of Physics, University of Warsaw, Warsaw, Poland
H. Pawlowska
CORRESPONDING AUTHOR
Institute of Geophysics, Faculty of Physics, University of Warsaw, Warsaw, Poland
W. W. Grabowski
National Center for Atmospheric Research (NCAR), Boulder, CO, USA
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In clouds, collisional breakup occurs when two colliding droplets splinter into new, smaller fragments. Particle-based modeling approaches often do not represent breakup because of the computational demands of creating new droplets. We present a particle-based breakup method that preserves the computational efficiency of these methods. In a series of simple demonstrations, we show that this representation alters cloud processes in reasonable and expected ways.
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In systems such as atmospheric clouds, droplets undergo growth through condensation of vapor. The broadness of the resultant size spectrum of droplets influences precipitation likelihood and the radiative properties of clouds. One of the inherent limitations of simulations of the problem is the so-called numerical diffusion causing overestimation of the spectrum width, hence the term numerical broadening. In the paper, we take a closer look at one of the algorithms used in this context: MPDATA.
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In systems such as atmospheric clouds, droplets undergo growth through condensation of vapor. The broadness of the resultant size spectrum of droplets influences precipitation likelihood and the radiative properties of clouds. One of the inherent limitations of simulations of the problem is the so-called numerical diffusion causing overestimation of the spectrum width, hence the term numerical broadening. In the paper, we take a closer look at one of the algorithms used in this context: MPDATA.
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Lois Thomas, Wojciech W. Grabowski, and Bipin Kumar
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Lois Thomas, Neelam Malap, Wojciech W. Grabowski, Kundan Dani, and Thara V. Prabha
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Wojciech W. Grabowski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 11, 103–120, https://doi.org/10.5194/gmd-11-103-2018, https://doi.org/10.5194/gmd-11-103-2018, 2018
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This paper introduces a novel approach to simulating ice-free clouds. The key process is formation and transport of cloud droplets that are represented through Lagrangian particles referred to as super-droplets. Each super-droplet represents a multitude of natural cloud droplets. The essential component of the scheme that makes it different and more efficient from previous approaches is the presence of super-droplets only within a cloud.
Piotr Dziekan and Hanna Pawlowska
Atmos. Chem. Phys., 17, 13509–13520, https://doi.org/10.5194/acp-17-13509-2017, https://doi.org/10.5194/acp-17-13509-2017, 2017
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Raindrops form when small cloud droplets collide with each other. In most computer models of clouds, this process is described using the Smoluchowski equation. We compare the Smoluchowski equation with computer simulations in which each droplet within a small part of the cloud is modeled. We show, depending on the simulation setup, that the Smoluchowski equation can give overly slow or fast rain formation. This implies that many cloud models used do not correctly represent rain formation.
Sylwester Arabas and Shin-ichiro Shima
Nonlin. Processes Geophys., 24, 535–542, https://doi.org/10.5194/npg-24-535-2017, https://doi.org/10.5194/npg-24-535-2017, 2017
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The paper bridges cloud/aerosol modelling with bifurcation analysis. It identifies two nonlinear peculiarities in the differential equations describing formation of atmospheric clouds through vapour condensation on a population of aerosol particles. A key finding of the paper is an analytic estimate for the timescale of the process. The study emerged from discussions on the causes of hysteretic behaviour of the system that we observed in the results of numerical simulations.
Muhammad E. E. Hassim, W. W. Grabowski, and T. P. Lane
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-402, https://doi.org/10.5194/acp-2016-402, 2016
Revised manuscript not accepted
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Model simulations show that there is more surface rainfall, less shallow clouds below 3 km and more deep clouds above 9 km in pristine air conditions than in a polluted environment, contrary to previous studies. This is due to more efficient rain processes below the freezing level, enhanced ice growth above and the off-loading of precipitation that increases cloud buoyancy aloft. Our results demonstrate that microphysical effects dominate the aerosol impact on rainfall more than cloud dynamics.
M. E. E. Hassim, T. P. Lane, and W. W. Grabowski
Atmos. Chem. Phys., 16, 161–175, https://doi.org/10.5194/acp-16-161-2016, https://doi.org/10.5194/acp-16-161-2016, 2016
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Gravity waves from deep convection along with terrain and coastal effects control the development and movement of squall lines that affect the diurnal cycle of rainfall over New Guinea and its northern coast. Days with offshore propagating systems are governed by background conditions (more mid-tropospheric moisture, CAPE, and low-level convergence) as opposed to days without offshore propagation. Our results shed some light on the physics and dynamics of Maritime Continent organised convection
A. Jaruga, S. Arabas, D. Jarecka, H. Pawlowska, P. K. Smolarkiewicz, and M. Waruszewski
Geosci. Model Dev., 8, 1005–1032, https://doi.org/10.5194/gmd-8-1005-2015, https://doi.org/10.5194/gmd-8-1005-2015, 2015
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This paper accompanies the first release of libmpdata++, a C++ library implementing the multidimensional positive-definite advection transport algorithm (MPDATA) on a regular structured grid. The library offers basic numerical solvers for systems of generalised transport equations. All solvers offer parallelisation through domain decomposition using shared-memory parallelisation. The paper describes the library programming interface, and serves as a user guide.
W. W. Grabowski, L.-P. Wang, and T. V. Prabha
Atmos. Chem. Phys., 15, 913–926, https://doi.org/10.5194/acp-15-913-2015, https://doi.org/10.5194/acp-15-913-2015, 2015
D. Jarecka, H. Pawlowska, W. W. Grabowski, and A. A. Wyszogrodzki
Atmos. Chem. Phys., 13, 8489–8503, https://doi.org/10.5194/acp-13-8489-2013, https://doi.org/10.5194/acp-13-8489-2013, 2013
A. A. Wyszogrodzki, W. W. Grabowski, L.-P. Wang, and O. Ayala
Atmos. Chem. Phys., 13, 8471–8487, https://doi.org/10.5194/acp-13-8471-2013, https://doi.org/10.5194/acp-13-8471-2013, 2013
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
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We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
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A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in 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's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
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In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
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A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
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We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
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
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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.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
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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.
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
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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
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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
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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
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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
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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
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow 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
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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
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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.
Álvaro González-Cervera and Luis Durán
EGUsphere, https://doi.org/10.5194/egusphere-2024-958, https://doi.org/10.5194/egusphere-2024-958, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the Analog Method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities of broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-84, https://doi.org/10.5194/gmd-2024-84, 2024
Revised manuscript accepted for GMD
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We apply a comprehensive approach to select a subset of CMIP6 that is suitable for dynamical downscaling over Southeast Asia by considering model performance, model independence, data availability, and future climate change spread. The standardised benchmarking framework is applied to identify a subset of models through two stages of assessment: statistical-based and process-based metrics. We finalize a sub-set of two independent models for dynamical downscaling over Southeast Asia.
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
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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.
Cited articles
Ahnert, K. and Mulansky, M.: Boost.Numeric.Odeint: solving ordinary differential equations, in: Boost Library Documentation, available at: http://www.boost.org/doc/libs/ (last access: 15 November 2014), 2013.
Allen, G., Coe, H., Clarke, A., Bretherton, C., Wood, R., Abel, S. J., Barrett, P., Brown, P., George, R., Freitag, S., McNaughton, C., Howell, S., Shank, L., Kapustin, V., Brekhovskikh, V., Kleinman, L., Lee, Y.-N., Springston, S., Toniazzo, T., Krejci, R., Fochesatto, J., Shaw, G., Krecl, P., Brooks, B., McMeeking, G., Bower, K. N., Williams, P. I., Crosier, J., Crawford, I., Connolly, P., Allan, J. D., Covert, D., Bandy, A. R., Russell, L. M., Trembath, J., Bart, M., McQuaid, J. B., Wang, J., and Chand, D.: South East Pacific atmospheric composition and variability sampled along 20° S during VOCALS-REx, Atmos. Chem. Phys., 11, 5237–5262, https://doi.org/10.5194/acp-11-5237-2011, 2011.
Andrejczuk, M., Reisner, J., Henson, B., Dubey, M., and Jeffery, C.: The potential impacts of pollution on a nondrizzling stratus deck: does aerosol number matter more than type?, J. Geophys. Res., 113, D19204, https://doi.org/10.1029/2007JD009445, 2008.
Andrejczuk, M., Grabowski, W., Reisner, J., and Gadian, A.: Cloud-aerosol interactions for boundary layer stratocumulus in the Lagrangian Cloud Model, J. Geophys. Res., 115, D22214, https://doi.org/10.1029/2010JD014248, 2010.
Arabas, S. and Pawlowska, H.: Adaptive method of lines for multi-component aerosol condensational growth and CCN activation, Geosci. Model Dev., 4, 15–31, https://doi.org/10.5194/gmd-4-15-2011, 2011.
Arabas, S. and Shima, S.: Large Eddy simulations of trade-wind cumuli using particle-based microphysics with Monte-Carlo coalescence, J. Atmos. Sci., 70, 2768–2777, https://doi.org/10.1175/JAS-D-12-0295.1, 2013.
Bott, A.: A flux method for the numerical solution of the stochastic collection equation, J. Atmos. Sci., 55, 2284–2293, https://doi.org/10.1175/1520-0469(1998)055< 2284:AFMFTN> 2.0.CO;2, 1998.
Brokken, F.: C++ Annotations, Center of Information Technology, University of Groningen, available at: http://cppannotations.sf.net/ (last access: 15 November 2014), 2013.
Bryan, G.: On the computation of pseudoadiabatic entropy and equivalent potential temperature, Mon. Weather Rev., 136, 5239–5245, https://doi.org/10.1175/2008MWR2593.1, 2008.
Castellano, N. E. and Ávila, E. E.: Vapour density field of a population of cloud droplets, J. Atmos. Sol.-Terr. Phys., 73, 2423–2428, https://doi.org/10.1016/j.jastp.2011.08.013, 2011.
Clift, R., Grace, J., and Weber, M.: Bubbles, Drops, and Particles, Academic Press, New York, 1978, reprinted by Dover Publications, 2005.
Crowe, C., Schwarzkopf, J., Sommerfeld, M., and Tsuji, Y.: Multiphase flows with droplets and particles, 2nd edn., CRC Press, Boca Raton, FL, USA, 2012.
Curry, J. and Webster, P.: Thermodynamics of Atmospheres and Oceans, Academic Press, 1999.
Duarte, M., Almgren, A., Balakrishnan, K., Bell, J., and Romps, D.: A Numerical Study of Methods for Moist Atmospheric Flows: Compressible Equations, Mon. Weather Rev., 142, 4269–4283, https://doi.org/10.1175/MWR-D-13-00368.1, 2014.
Easterbrook, S. M. and Johns, T. C.: Engineering the software for understanding climate change, Comput. Sci. Eng., 11, 65–74, https://doi.org/10.1109/MCSE.2009.193, 2009.
Fernández-Díaz, J. M., Braña, M. A. R., García, B. A., Muñiz, C. G.-P., and Nieto, P. J. G.: The goodness of the internally mixed aerosol assumption under condensation-evaporation, Aerosol Sci. Tech., 31, 17–23, https://doi.org/10.1080/027868299304327, 1999.
Golaz, J.-C., Larson, V., and Cotton, W.: A PDF-based model for boundary layer clouds. Part 1: 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.
Grabowski, W. and Smolarkiewicz, P.: Monotone finite-difference approximations to the advection-condensation problem, Mon. Weather Rev., 118, 2082–2097, https://doi.org/10.1175/1520-0493(1990)118<2082:MFDATT>2.0.CO;2, 1990.
Grabowski, W. and Smolarkiewicz, P.: Two-time-level semi-lagrangian modeling of precipitating clouds, Mon. Weather Rev., 124, 487–497, https://doi.org/10.1175/1520-0493(1996)124<0487:TTLSLM>2.0.CO;2, 1996.
Grabowski, W. and Smolarkiewicz, P.: A multiscale anelastic model for meteorological research, Mon. Weather Rev., 130, 939–956, https://doi.org/10.1175/1520-0493(2002)130<0939:AMAMFM>2.0.CO;2, 2002.
Grabowski, W. W. and Wang, L.-P.: Growth of cloud droplets in a turbulent environment, Annu. Rev. Fluid Mech., 45, 293–324, https://doi.org/10.1146/annurev-fluid-011212-140750, 2013.
Hoberock, J. and Bell, N.: Thrust: a parallel template library, available at: http://thrust.github.io/ (last access: 15 November 2014), 2010.
Ince, D., Hatton, L., and Graham-Cumming, J.: The case for open computer programs, Nature, 482, 485–488, https://doi.org/10.1038/nature10836, 2012.
Jarecka, D., Grabowski, W., Morrison, H., and Pawlowska, H.: Homogeneity of the subgrid-scale turbulent mixing in large-Eddy simulation of shallow convection, J. Atmos. Sci., 70, 2751–2767, https://doi.org/10.1175/JAS-D-13-042.1, 2013.
Jarecka, D., Arabas, S., and Del Vento, D.: Python bindings for libcloudph++, arXiv:1504.01161, 2015.
Jaruga, A., Arabas, S., Jarecka, D., Pawlowska, H., Smolarkiewicz, P. K., and Waruszewski, M.: libmpdata++ 1.0: a library of parallel MPDATA solvers for systems of generalised transport equations, Geosci. Model Dev., 8, 1005–1032, https://doi.org/10.5194/gmd-8-1005-2015, 2015.
Kessler, E.: On the continuity and distribution of water substance in atmospheric circulations, Atmos. Res., 38, 109–145, https://doi.org/10.1016/0169-8095(94)00090-Z, 1995.
Khairoutdinov, M. and Kogan, Y.: A new cloud physics parameterization in a large-Eddy simulation model of marine stratocumulus, Mon. Weather Rev., 128, 229–243, https://doi.org/10.1175/1520-0493(2000)128<0229:ANCPPI>2.0.CO;2, 2000.
Khvorostyanov, V. and Curry, J.: Terminal velocities of droplets and crystals: power laws with continuous parameters over the size spectrum, J. Atmos. Sci., 59, 1872–1884, https://doi.org/10.1175/1520-0469(2002)059<1872:TVODAC>2.0.CO;2, 2002.
Khvorostyanov, V. and Curry, J.: Aerosol size spectra and CCN activity spectra: Reconciling the lognormal, algebraic, and power laws, J. Geophys. Res., 111, D12202, https://doi.org/10.1029/2005JD006532, 2006.
Laaksonen, A., Vesala, T., Kulmala, M., Winkler, P. M., and Wagner, P. E.: Commentary on cloud modelling and the mass accommodation coefficient of water, Atmos. Chem. Phys., 5, 461–464, https://doi.org/10.5194/acp-5-461-2005, 2005.
Lebo, Z. J. and Seinfeld, J. H.: A continuous spectral aerosol-droplet microphysics model, Atmos. Chem. Phys., 11, 12297–12316, https://doi.org/10.5194/acp-11-12297-2011, 2011.
Marcolli, C., Luo, B. P., Peter, Th., and Wienhold, F. G.: Internal mixing of the organic aerosol by gas phase diffusion of semivolatile organic compounds, Atmos. Chem. Phys., 4, 2593–2599, https://doi.org/10.5194/acp-4-2593-2004, 2004.
Matsumoto, M. and Nishimura, T.: Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator, ACM T. Model. Comput. S., 8, 3–30, https://doi.org/10.1145/272991.272995, 1998.
Mayer, B. and Kylling, A.: Technical note: The libRadtran software package for radiative transfer calculations – description and examples of use, Atmos. Chem. Phys., 5, 1855–1877, https://doi.org/10.5194/acp-5-1855-2005, 2005.
McFarquhar, G.: Raindrop size distribution and evolution, in: Rainfall: State of the Science, edited by: Testik, F. Y. and Gebremichael, M., Washington, D.C., USA, AGU, 49–59, https://doi.org/10.1029/GM191, 2010.
Mitra, S., Brinkmann, J., and Pruppacher, H.: A wind tunnel study on the drop-to-particle conversion, J. Aerosol Sci., 23, 245–256, https://doi.org/10.1016/0021-8502(92)90326-Q, 1992.
Morin, A., Urban, J., Adams, P., Foster, I., Sali, A., Baker, D., and Sliz, P.: Shining light into black boxes, Science, 336, 159–160, https://doi.org/10.1126/science.1218263, 2012.
Morrison, H. and Grabowski, W.: Comparison of bulk and bin warm-rain microphysics models using a kinematic framework, J. Atmos. Sci., 64, 2839–2861, https://doi.org/10.1175/JAS3980, 2007.
Morrison, H. and Grabowski, W.: Modeling supersaturation and subgrid-scale mixing with two-moment bulk warm microphysics, J. Atmos. Sci., 65, 792–812, https://doi.org/10.1175/2007JAS2374.1, 2008.
Morrison, H., Curry, J., and Khvorostyanov, V.: A new double-moment microphysics parameterization for application in cloud and climate models. Part 1: Description, J. Atmos. Sci., 62, 1665–1677, https://doi.org/10.1175/JAS3446.1, 2005.
Muhlbauer, A., Grabowski, W. W., Malinowski, S. P., Ackerman, T. P., Bryan, G. H., Lebo, Z. J., Milbrandt, J. A., Morrison, H., Ovchinnikov, M., Tessendorf, S., Thériault, J. M., and Thompson, G.: Reexamination of the State-of-the-art of cloud modeling shows real improvements, B. Am. Meteorol. Soc., 94, ES45–ES48, https://doi.org/10.1175/BAMS-D-12-00188.1, 2013.
Ogura, Y. and Takahashi, T.: Numerical simulation of the life cycle of a thunderstorm cell, Mon. Weather Rev., 99, 895–911, https://doi.org/10.1175/1520-0493(1971)099<0895:NSOTLC>2.3.CO;2, 1971.
Pennell, C. and Reichler, T.: On the effective number of climate models, J. Climate, 24, 2358–2367, https://doi.org/10.1175/2010JCLI3814.1, 2010.
Petters, M. D. and Kreidenweis, S. M.: A single parameter representation of hygroscopic growth and cloud condensation nucleus activity, Atmos. Chem. Phys., 7, 1961–1971, https://doi.org/10.5194/acp-7-1961-2007, 2007.
Rasinski, P., Pawlowska, H., and Grabowski, W.: Observations and kinematic modeling of drizzling marine stratocumulus, Atmos. Res., 102, 120–135, https://doi.org/10.1016/j.atmosres.2011.06.020, 2011.
Riechelmann, T., Noh, Y., and Raasch, S.: A new method for large-eddy simulations of clouds with Lagrangian droplets including the effects of turbulent collision, New J. Phys., 14, 065008, https://doi.org/10.1088/1367-2630/14/6/065008, 2012.
Rogers, J. and Davis, R.: The effects of van der Waals attractions on cloud droplet growth by coalescence, J. Atmos. Sci., 47, 1075–1080, https://doi.org/10.1175/1520-0469(1990)047<1075:TEOVDW>2.0.CO;2, 1990.
Schabel, M. and Watanabe, S.: Boost.Units: Zero-overhead dimensional analysis and unit/quantity manipulation and conversion, in: Boost Library Documentation, available at: http://www.boost.org/doc/libs/ (last access: 15 November 2014), 2008.
Shima, S., Sugiyama, T., Kusano, K., Kawano, A., and Hirose, S.: Simulation method, simulation program, and simulator, European Patent EP1847939, 2007.
Shima, S., Kusano, K., Kawano, A., Sugiyama, T., and Kawahara, S.: The super-droplet method for the numerical simulation of clouds and precipitation: a particle-based and probabilistic microphysics model coupled with a non-hydrostatic model, Q. J. Roy. Meteorol. Soc., 135, 1307–1320, https://doi.org/10.1002/qj.441, 2009.
Simmel, M., Trautmann, T., and Tetzlaff, G.: Numerical solution of the stochastic collection equation – comparison of the Linear Discrete Method with other methods, Atmos. Res., 61, 135–148, https://doi.org/10.1016/S0169-8095(01)00131-4, 2002.
Slawinska, J., Grabowski, W. W., and Morrison, H.: The impact of atmospheric aerosols on precipitation from deep organized convection: a prescribed-flow model study using double-moment bulk microphysics, Q. J. Roy. Meteorol. Soc., 135, 1906–1913, https://doi.org/10.1002/qj.450, 2009.
Smolarkiewicz, P.: Multidimensional positive definite advection transport algorithm: an overview, Int. J. Numer. Meth. Fl., 50, 1123–1144, https://doi.org/10.1002/fld.1071, 2006.
Smolík, J., Džumbová, L., Schwarz, J., and Kulmala, M.: Evaporation of ventilated water droplet: connection between heat and mass transfer, J. Aerosol Sci., 32, 739–748, https://doi.org/10.1016/S0021-8502(00)00118-X, 2001.
Sölch, I. and Kärcher, B.: A large-eddy model for cirrus clouds with explicit aerosol and ice microphysics and Lagrangian ice particle tracking, Q. J. Roy. Meteorol. Soc., 136, 2074–2093, https://doi.org/10.1002/qj.689, 2010.
Stevens, B. and Feingold, G.: Untangling aerosol effects on clouds and precipitation in a buffered system, Nature, 461, 607–613, https://doi.org/10.1038/nature08281, 2009.
Straka, J.: Cloud and Precipitation Microphysics: Principles and Parameterizations, Cambridge University Press, 2009.
Szakáll, M., Mitra, S. K., Diehl, K., and Borrmann, S.: Shapes and oscillations of falling raindrops – a review, Atmos. Res., 97, 416–425, https://doi.org/10.1016/j.atmosres.2010.03.024, 2010.
Szumowski, M., Grabowski, W., and Ochs III, H.: Simple two-dimensional kinematic framework designed to test warm rain microphysical models, Atmos. Res., 45, 299–326, https://doi.org/10.1016/S0169-8095(97)00082-3, 1998.
Unterstrasser, S. and Sölch, I.: Optimisation of the simulation particle number in a Lagrangian ice microphysical model, Geosci. Model Dev., 7, 695–709, https://doi.org/10.5194/gmd-7-695-2014, 2014.
Vaillancourt, P., Yau, M., and Grabowski, W.: Microscopic approach to cloud droplet growth by condensation. Part I: Model description and results without turbulence, J. Atmos. Sci., 58, 1945–1964, https://doi.org/10.1175/1520-0469(2001)058<1945:MATCDG>2.0.CO;2, 2001.
Vallis, G.: Atmospheric and oceanic fluid dynamics: fundamentals and large-scale circulation, Cambridge University Press, Cambridge, 2006.
Veldhuizen, T.: Blitz++ User's Guide: a C++ class library for scientific computing, version 0.9, available at: http://blitz.sf.net/resources/blitz-0.9.pdf (last access: 15 November 2014), 2005.
Vohl, O., Mitra, S., Wurzler, S., Diehl, K., and Pruppacher, H.: Collision efficiencies empirically determined from laboratory investigations of collisional growth of small raindrops in a laminar flow field, Atmos. Res., 85, 120–125, https://doi.org/10.1016/j.atmosres.2006.12.001, 2007.
Wilson, G., Aruliah, D. A., Titus Brown, C., Chue Hong, N. P., Davis, M., Guy, R. T., Haddock, S. H. D., Huff, K., Mitchell, I. M., Plumbley, M., Waugh, B., White, E. P., and Wilson, P.: Best practices for scientific computing, PLoS Biol., 12, e1001745, https://doi.org/10.1371/journal.pbio.1001745, 2014.
Wood, R.: Drizzle in stratiform boundary layer clouds. Part II: Microphysical aspects, J. Atmos. Sci., 62, 3034–3050, https://doi.org/10.1175/JAS3530.1, 2005.
Short summary
This paper introduces a free and open-source C++ library of algorithms for representing cloud microphysics in numerical models. In the current release, the library covers three warm-rain schemes: the single- and double-moment bulk schemes, and the particle-based scheme with Monte Carlo coalescence. The three schemes are intended for modelling frameworks of different dimensionalities and complexities ranging from parcel models to multi-dimensional cloud-resolving (e.g. large-eddy) simulations.
This paper introduces a free and open-source C++ library of algorithms for representing cloud...
