scholarly journals libcloudph++ 1.1: aqueous phase chemistry extension of the Lagrangian cloud microphysics scheme

2018 ◽  
Author(s):  
Anna Jaruga ◽  
Hanna Pawlowska

Abstract. This paper introduces a new scheme available in the library of algorithms for representing cloud microphysics in numerical models named libcloudph++. The scheme extends the Lagrangian microphysics scheme available in libcloudph++ to the aqueous phase chemical processes occurring within cloud droplets. The representation of chemical processes focuses on the aqueous phase oxidation of the dissolved SO2 by O3 and H2O2. The Lagrangian Microphysics and Chemistry (LMC) scheme allows tracking the changes in the cloud condensation nuclei (CCN) distribution caused by both collisions between cloud droplets and aqueous phase oxidation. The scheme is implemented in C++ and equipped with bindings to Python which allow reusing the created scheme from models implemented in other programming languages. The scheme can be used on either CPU or GPU, and is distributed under the GPL3 license. Here, the LMC scheme is tested in a simple 0-dimensional adiabatic parcel model and then used in a 2-dimensional prescribed flow framework. The results are discussed with the focus on changes to the CCN sizes and compared with other model simulations discussed in the literature.

2018 ◽  
Vol 11 (9) ◽  
pp. 3623-3645 ◽  
Author(s):  
Anna Jaruga ◽  
Hanna Pawlowska

Abstract. This paper introduces a new scheme available in the library of algorithms for representing cloud microphysics in numerical models named libcloudph++. The scheme extends the particle-based microphysics scheme with a Monte Carlo coalescence available in libcloudph++ to the aqueous-phase chemical processes occurring within cloud droplets. The representation of chemical processes focuses on the aqueous-phase oxidation of the dissolved SO2 by O3 and H2O2. The particle-based microphysics and chemistry scheme allows for tracking of the changes in the cloud condensation nuclei (CCN) distribution caused by both collisions between cloud droplets and aqueous-phase oxidation. The scheme is implemented in C++ and equipped with bindings to Python. The scheme can be used on either a CPU or a GPU, and is distributed under the GPLv3 license. Here, the particle-based microphysics and chemistry scheme is tested in a simple 0-dimensional adiabatic parcel model and then used in a 2-dimensional prescribed flow framework. The results are discussed with a focus on changes to the CCN sizes and comparison with other model simulations discussed in the literature.


2013 ◽  
Vol 13 (3) ◽  
pp. 1177-1192 ◽  
Author(s):  
C. Knote ◽  
D. Brunner

Abstract. Clouds are reaction chambers for atmospheric trace gases and aerosols, and the associated precipitation is a major sink for atmospheric constituents. The regional chemistry-climate model COSMO-ART has been lacking a description of wet scavenging of gases and aqueous-phase chemistry. In this work we present a coupling of COSMO-ART with a wet scavenging and aqueous-phase chemistry scheme. The coupling is made consistent with the cloud microphysics scheme of the underlying meteorological model COSMO. While the choice of the aqueous-chemistry mechanism is flexible, the effects of a simple sulfur oxidation scheme are shown in the application of the coupled system in this work. We give details explaining the coupling and extensions made, then present results from idealized flow-over-hill experiments in a 2-D model setup and finally results from a full 3-D simulation. Comparison against measurement data shows that the scheme efficiently reduces SO2 trace gas concentrations by 0.3 ppbv (−30%) on average, while leaving O3 and NOx unchanged. PM10 aerosol mass was increased by 10% on average. While total PM2.5 changes only little, chemical composition is improved notably. Overestimations of nitrate aerosols are reduced by typically 0.5–1 μg m−3 (up to −2 μg m−3 in the Po Valley) while sulfate mass is increased by 1–1.5 μg m−3 on average (up to 2.5 μg m−3 in Eastern Europe). The effect of cloud processing of aerosols on its size distribution, i.e. a shift towards larger diameters, is observed. Compared against wet deposition measurements the system tends to underestimate the total wet deposited mass for the simulated case study.


2012 ◽  
Vol 12 (10) ◽  
pp. 26099-26142
Author(s):  
C. Knote ◽  
D. Brunner

Abstract. Clouds are reaction chambers for atmospheric trace gases and aerosols, and the associated precipitation is a major sink for atmospheric constituents. The regional chemistry-climate model COSMO-ART has been lacking a description of wet scavenging of gases and aqueous-phase chemistry. In this work we present a coupling of COSMO-ART with a wet scavenging and aqueous-phase chemistry scheme. The coupling is made consistent with the cloud microphysics scheme of the underlying meteorological model COSMO. While the choice of the aqueous-chemistry mechanism is flexible, the effects of a simple sulfur oxidation scheme are shown in the application of the coupled system in this work. We give details explaining the coupling and extensions made, then present results from idealized flow-over-hill experiments in a 2-D model setup and finally results from a full 3-D simulation. Comparison against measurement data shows that the scheme efficiently reduces SO2 trace gas concentrations by 0.3 ppbv (−30%) on average, while leaving O3 and NOx unchanged. PM10 aerosol mass, which has been overestimated previously, is now in much better agreement with measured values due to a stronger scavenging of coarse particles. While total PM2.5 changes only little, chemical composition is improved notably. Overestimations of nitrate aerosols are reduced by typically 0.5–1 μg m−3 (up to −2 μg m−3 in the Po Valley) while sulfate mass is increased by 1–1.5 μg m−3 on average (up to 2.5 μg m−3 in Eastern Europe). The effect of cloud processing of aerosols on its size distribution, i. e. a shift towards larger diameters, is observed. Compared against wet deposition measurements the system underestimates the total wet deposited mass for the simulated case study. We find that while evaporation of cloud droplets dominates in higher altitudes, evaporation of precipitation can contribute up to 50% of total evaporated mass near the surface.


2021 ◽  
Vol 21 (21) ◽  
pp. 16093-16120
Author(s):  
Wendong Ge ◽  
Junfeng Liu ◽  
Kan Yi ◽  
Jiayu Xu ◽  
Yizhou Zhang ◽  
...  

Abstract. Sulfur dioxide (SO2) is a major atmospheric pollutant and precursor of sulfate aerosols, which influences air quality, cloud microphysics, and climate. Therefore, better understanding the conversion of SO2 to sulfate is essential to simulate and predict sulfur compounds more accurately. This study evaluates the effects of in-cloud aqueous-phase chemistry on SO2 oxidation in the Community Earth System Model version 2 (CESM2). We replaced the default parameterized SO2 aqueous-phase reactions with detailed HOx, Fe, N, and carbonate chemistry in cloud droplets and performed a global simulation for 2014–2015. Compared with the observations, the results incorporating detailed cloud aqueous-phase chemistry greatly reduced SO2 overestimation. This overestimation was reduced by 0.1–10 ppbv (parts per billion by volume) in most of Europe, North America, and Asia and more than 10 ppbv in parts of China. The biases in annual simulated SO2 mixing ratios decreased by 46 %, 41 %, and 22 % in Europe, the USA, and China, respectively. Fe chemistry and HOx chemistry contributed more to SO2 oxidation than N chemistry. Higher concentrations of soluble Fe and higher pH values could further enhance the oxidation capacity. This study emphasizes the importance of detailed in-cloud aqueous-phase chemistry for the oxidation of SO2. These mechanisms can improve SO2 simulation in CESM2 and deepen understanding of SO2 oxidation and sulfate formation.


2019 ◽  
Author(s):  
Jiarong Li ◽  
Chao Zhu ◽  
Hui Chen ◽  
Defeng Zhao ◽  
Likun Xue ◽  
...  

Abstract. The influence of aerosols, both natural and anthropogenic, remains a major area of uncertainty when predicting the properties and behaviour of clouds and their influence on climate. In an attempt to understand better the microphysical properties of cloud droplets, the aerosol-cloud interactions, and the corresponding climate effect during cloud life cycles in the North China Plain, an intensive observation took place from 17 June to 30 July 2018 at the summit of Mt. Tai. Cloud microphysical parameters were monitored simultaneously with number concentrations of cloud condensation nuclei (NCCN) at different supersaturations, PM2.5 mass concentrations, particle size distributions and meteorological parameters. Number concentrations of cloud droplets (NC), liquid water content (LWC) and effective radius of cloud droplets (reff) show large variations among 40 cloud events observed during the campaign. Perturbations of aerosols will significantly increase the NC of cloud droplets and shift cloud droplets toward smaller size ranges. Clouds in clean days are more susceptible to the change in concentrations of particle number (NP). LWC shows positive correlation with reff. As NC increases, reff changes from a trimodal distribution to a unimodal distribution. By assuming a cloud thickness of 100 m, we find that the albedo can increase 36.4 % if the cloud gets to be disturbed by aerosols. This may induce a cooling effect on the local climate system. Our results contribute more information about regional cloud microphysics and will help to reduce the uncertainties in climate models when predicting climate responses to cloud-aerosol interactions.


2013 ◽  
Vol 30 (12) ◽  
pp. 2896-2906 ◽  
Author(s):  
J. Mielikainen ◽  
B. Huang ◽  
H.-L. A. Huang ◽  
M. D. Goldberg ◽  
A. Mehta

Abstract The Weather Research and Forecasting model (WRF) double-moment 6-class microphysics scheme (WDM6) implements a double-moment bulk microphysical parameterization of clouds and precipitation and is applicable in mesoscale and general circulation models. WDM6 extends the WRF single-moment 6-class microphysics scheme (WSM6) by incorporating the number concentrations for cloud and rainwater along with a prognostic variable of cloud condensation nuclei (CCN) number concentration. Moreover, it predicts the mixing ratios of six water species (water vapor, cloud droplets, cloud ice, snow, rain, and graupel), similar to WSM6. This paper describes improving the computational performance of WDM6 by exploiting its inherent fine-grained parallelism using the NVIDIA graphics processing unit (GPU). Compared to the single-threaded CPU, a single GPU implementation of WDM6 obtains a speedup of 150× with the input/output (I/O) transfer and 206× without the I/O transfer. Using four GPUs, the speedup reaches 347× and 715×, respectively.


2020 ◽  
Author(s):  
Gustavo Abade ◽  
Marta Waclawczyk ◽  
Wojciech W. Grabowski ◽  
Hanna Pawlowska

<p>Turbulent clouds are challenging to model and simulate due to uncertainties in microphysical processes occurring at unresolved subgrid scales (SGS). These processes include the transport of cloud particles, supersaturation fluctuations, turbulent mixing, and the resulting stochastic droplet activation and growth by condensation. In this work, we apply two different Lagrangian stochastic schemes to model SGS cloud microphysics. Collision and coalescence of droplets are not considered. Cloud droplets and unactivated cloud condensation nuclei (CCN) are described by Lagrangian particles (superdroplets). The first microphysical scheme directly models the supersaturation fluctuations experienced by each Lagrangian superdroplet as it moves with the air flow. Supersaturation fluctuations are driven by turbulent fluctuations of the droplet vertical velocity through the adiabatic cooling/warming effect. The second, more elaborate scheme uses both temperature and vapor mixing ratio as stochastic attributes attached to each superdroplet. It is based on the probability density function formalism that provides a consistent Eulerian-Lagrangian formulation of scalar transport in a turbulent flow. Both stochastic microphysical schemes are tested in a synthetic turbulent-like cloud flow that mimics a stratocumulus topped boundary layer. It is shown that SGS turbulence plays a key role in broadening the droplet-size distribution towards larger sizes. Also, the feedback on water vapor of stochastically activated droplets buffers the variations of the mean supersaturation driven the resolved transport. This extends the distance over which entrained CNN are activated inside the cloud layer and produces multimodal droplet-size distributions.</p>


2016 ◽  
Vol 16 (3) ◽  
pp. 1693-1712 ◽  
Author(s):  
C. R. Hoyle ◽  
C. Fuchs ◽  
E. Järvinen ◽  
H. Saathoff ◽  
A. Dias ◽  
...  

Abstract. The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and −10 °C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion – pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and −10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, super-cooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 °C is correct.


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