Author response to comments on acp-2022-273 Article Swipe
Abstract. We carried out a closure study of aerosolâcloud interactions during stratocumulus formation using a large eddy simulation model UCLALESâSALSA (University of California Los Angeles large eddy simulation modelâsectional aerosol module for large applications) and observations from the 2020 cloud sampling campaign at Puijo SMEAR IV (Station for Measuring EcosystemâAtmosphere Relations) in Kuopio, Finland. The unique observational setup combining in situ and cloud remote sensing measurements allowed a closer look into the aerosol sizeâcomposition dependence of droplet activation and droplet growth in turbulent boundary layer driven by surface forcing and radiative cooling. UCLALESâSALSA uses spectral bin microphysics for aerosols and hydrometeors, and incorporates a full description of their interactions into the turbulent-convective radiation-dynamical model of stratocumulus. Based on our results, the model successfully described the probability distribution of updraught velocities and consequently the size dependency of aerosol activation into cloud droplets, and further recreated the size distributions for both interstitial aerosol and cloud droplets. This is the first time such a detailed closure is achieved not only accounting for activation of cloud droplets in different updraughts, but also accounting for processes evaporating droplets and drizzle production through coagulationâcoalescence. We studied two cases of cloud formation, one diurnal (24 September 2020) and one nocturnal (31 October 2020), with high and low aerosol loadings, respectively. Aerosol number concentrations differ more than 1 order of magnitude between cases and therefore, lead to cloud droplet number concentration (CDNC) values which range from less than 100âcmâ3 up to 1000âcmâ3. Different aerosol loadings affected supersaturation at the cloud base, and thus the size of aerosol particles activating to cloud droplets. Due to higher CDNC, the mean size of cloud droplets in the diurnal high aerosol case was lower. Thus, droplet evaporation in downdraughts affected more the observed CDNC at Puijo altitude compared to the low aerosol case. In addition, in the low aerosol case, the presence of large aerosol particles in the accumulation mode played a significant role in the droplet spectrum evolution as it promoted the drizzle formation through collision and coalescence processes. Also, during the event, the formation of ice particles was observed due to subzero temperature at the cloud top. Although the modelled number concentration of ice hydrometeors was too low to be directly measured, the retrieval of hydrometeor sedimentation velocities with cloud radar allowed us to assess the realism of modelled ice particles. The studied cases are presented in detail and can be further used by the cloud modellers to test and validate their models in a well-characterized modelling setup. We also provide recommendations on how increasing amount of information on aerosol properties could improve the understanding of processes affecting cloud droplet number and liquid water content in stratiform clouds.
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Metadata
- Type
- peer-review
- Language
- en
- Landing Page
- https://doi.org/10.5194/acp-2022-273-ac1
- https://acp.copernicus.org/articles/22/12417/2022/acp-22-12417-2022.pdf
- OA Status
- gold
- References
- 86
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4290648563
All OpenAlex metadata
Raw OpenAlex JSON
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- DOI
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https://doi.org/10.5194/acp-2022-273-ac1Digital Object Identifier
- Title
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Author response to comments on acp-2022-273Work title
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peer-reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-08-08Full publication date if available
- Authors
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Silvia M. CalderónList of authors in order
- Landing page
-
https://doi.org/10.5194/acp-2022-273-ac1Publisher landing page
- PDF URL
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https://acp.copernicus.org/articles/22/12417/2022/acp-22-12417-2022.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://acp.copernicus.org/articles/22/12417/2022/acp-22-12417-2022.pdfDirect OA link when available
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Aerosol, Drizzle, Atmospheric sciences, Environmental science, Meteorology, Large eddy simulation, Cloud computing, Radiative transfer, Turbulence, Physics, Precipitation, Operating system, Quantum mechanics, Computer scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.case. | 303 |
| abstract_inverted_index.cases | 192, 225, 396 |
| abstract_inverted_index.cloud | 40, 63, 140, 153, 172, 194, 230, 254, 265, 275, 358, 382, 408, 441 |
| abstract_inverted_index.could | 434 |
| abstract_inverted_index.first | 158 |
| abstract_inverted_index.large | 16, 26, 33, 314 |
| abstract_inverted_index.layer | 85 |
| abstract_inverted_index.model | 19, 114, 122 |
| abstract_inverted_index.order | 221 |
| abstract_inverted_index.radar | 383 |
| abstract_inverted_index.range | 237 |
| abstract_inverted_index.setup | 58 |
| abstract_inverted_index.study | 7 |
| abstract_inverted_index.their | 108, 414 |
| abstract_inverted_index.using | 14 |
| abstract_inverted_index.water | 446 |
| abstract_inverted_index.which | 236 |
| abstract_inverted_index.(CDNC) | 234 |
| abstract_inverted_index.2020), | 206 |
| abstract_inverted_index.amount | 428 |
| abstract_inverted_index.assess | 387 |
| abstract_inverted_index.closer | 69 |
| abstract_inverted_index.detail | 400 |
| abstract_inverted_index.differ | 217 |
| abstract_inverted_index.driven | 86 |
| abstract_inverted_index.during | 11, 342 |
| abstract_inverted_index.event, | 344 |
| abstract_inverted_index.growth | 81 |
| abstract_inverted_index.higher | 269 |
| abstract_inverted_index.liquid | 445 |
| abstract_inverted_index.lower. | 284 |
| abstract_inverted_index.models | 415 |
| abstract_inverted_index.module | 31 |
| abstract_inverted_index.number | 215, 232, 363, 443 |
| abstract_inverted_index.played | 321 |
| abstract_inverted_index.remote | 64 |
| abstract_inverted_index.setup. | 420 |
| abstract_inverted_index.unique | 56 |
| abstract_inverted_index.values | 235 |
| abstract_inverted_index.<strong | 0 |
| abstract_inverted_index.Aerosol | 214 |
| abstract_inverted_index.Angeles | 25 |
| abstract_inverted_index.Kuopio, | 53 |
| abstract_inverted_index.aerosol | 30, 73, 137, 151, 211, 248, 261, 281, 302, 309, 315, 432 |
| abstract_inverted_index.allowed | 67, 384 |
| abstract_inverted_index.between | 224 |
| abstract_inverted_index.carried | 3 |
| abstract_inverted_index.closure | 6, 163 |
| abstract_inverted_index.clouds. | 450 |
| abstract_inverted_index.content | 447 |
| abstract_inverted_index.diurnal | 197, 279 |
| abstract_inverted_index.drizzle | 185, 334 |
| abstract_inverted_index.droplet | 77, 80, 231, 286, 327, 442 |
| abstract_inverted_index.forcing | 89 |
| abstract_inverted_index.further | 143, 404 |
| abstract_inverted_index.improve | 435 |
| abstract_inverted_index.provide | 423 |
| abstract_inverted_index.realism | 389 |
| abstract_inverted_index.sensing | 65 |
| abstract_inverted_index.studied | 190, 395 |
| abstract_inverted_index.subzero | 354 |
| abstract_inverted_index.surface | 88 |
| abstract_inverted_index.through | 187, 336 |
| abstract_inverted_index.(Station | 47 |
| abstract_inverted_index.Although | 360 |
| abstract_inverted_index.Finland. | 54 |
| abstract_inverted_index.achieved | 165 |
| abstract_inverted_index.aerosols | 99 |
| abstract_inverted_index.affected | 250, 290 |
| abstract_inverted_index.altitude | 297 |
| abstract_inverted_index.boundary | 84 |
| abstract_inverted_index.campaign | 42 |
| abstract_inverted_index.compared | 298 |
| abstract_inverted_index.cooling. | 92 |
| abstract_inverted_index.detailed | 162 |
| abstract_inverted_index.directly | 373 |
| abstract_inverted_index.droplets | 173, 183, 276 |
| abstract_inverted_index.loadings | 249 |
| abstract_inverted_index.modelled | 362, 391 |
| abstract_inverted_index.observed | 293, 351 |
| abstract_inverted_index.presence | 312 |
| abstract_inverted_index.promoted | 332 |
| abstract_inverted_index.results, | 120 |
| abstract_inverted_index.sampling | 41 |
| abstract_inverted_index.spectral | 95 |
| abstract_inverted_index.spectrum | 328 |
| abstract_inverted_index.validate | 413 |
| abstract_inverted_index.Different | 247 |
| abstract_inverted_index.Measuring | 49 |
| abstract_inverted_index.October | 205 |
| abstract_inverted_index.addition, | 305 |
| abstract_inverted_index.affecting | 440 |
| abstract_inverted_index.collision | 337 |
| abstract_inverted_index.combining | 59 |
| abstract_inverted_index.described | 124 |
| abstract_inverted_index.different | 175 |
| abstract_inverted_index.droplets, | 141 |
| abstract_inverted_index.droplets. | 154, 266 |
| abstract_inverted_index.evolution | 329 |
| abstract_inverted_index.formation | 13, 335, 346 |
| abstract_inverted_index.loadings, | 212 |
| abstract_inverted_index.magnitude | 223 |
| abstract_inverted_index.measured, | 374 |
| abstract_inverted_index.modellers | 409 |
| abstract_inverted_index.modelling | 419 |
| abstract_inverted_index.nocturnal | 203 |
| abstract_inverted_index.particles | 262, 316, 349 |
| abstract_inverted_index.presented | 398 |
| abstract_inverted_index.processes | 181, 439 |
| abstract_inverted_index.radiative | 91 |
| abstract_inverted_index.recreated | 144 |
| abstract_inverted_index.retrieval | 376 |
| abstract_inverted_index.turbulent | 83 |
| abstract_inverted_index.updraught | 129 |
| abstract_inverted_index.California | 23 |
| abstract_inverted_index.Relations) | 51 |
| abstract_inverted_index.accounting | 168, 179 |
| abstract_inverted_index.activating | 263 |
| abstract_inverted_index.activation | 78, 138, 170 |
| abstract_inverted_index.dependence | 75 |
| abstract_inverted_index.dependency | 135 |
| abstract_inverted_index.formation, | 195 |
| abstract_inverted_index.increasing | 427 |
| abstract_inverted_index.particles. | 393 |
| abstract_inverted_index.processes. | 340 |
| abstract_inverted_index.production | 186 |
| abstract_inverted_index.properties | 433 |
| abstract_inverted_index.simulation | 18, 28 |
| abstract_inverted_index.stratiform | 449 |
| abstract_inverted_index.therefore, | 227 |
| abstract_inverted_index.velocities | 130, 380 |
| abstract_inverted_index.(University | 21 |
| abstract_inverted_index.September | 199 |
| abstract_inverted_index.coalescence | 339 |
| abstract_inverted_index.description | 106 |
| abstract_inverted_index.evaporating | 182 |
| abstract_inverted_index.evaporation | 287 |
| abstract_inverted_index.hydrometeor | 378 |
| abstract_inverted_index.information | 430 |
| abstract_inverted_index.probability | 126 |
| abstract_inverted_index.significant | 323 |
| abstract_inverted_index.temperature | 355 |
| abstract_inverted_index.updraughts, | 176 |
| abstract_inverted_index.accumulation | 319 |
| abstract_inverted_index.consequently | 132 |
| abstract_inverted_index.distribution | 127 |
| abstract_inverted_index.downdraughts | 289 |
| abstract_inverted_index.hydrometeors | 367 |
| abstract_inverted_index.incorporates | 103 |
| abstract_inverted_index.interactions | 10, 109 |
| abstract_inverted_index.interstitial | 150 |
| abstract_inverted_index.measurements | 66 |
| abstract_inverted_index.microphysics | 97 |
| abstract_inverted_index.observations | 36 |
| abstract_inverted_index.successfully | 123 |
| abstract_inverted_index.applications) | 34 |
| abstract_inverted_index.concentration | 233, 364 |
| abstract_inverted_index.distributions | 147 |
| abstract_inverted_index.hydrometeors, | 101 |
| abstract_inverted_index.observational | 57 |
| abstract_inverted_index.respectively. | 213 |
| abstract_inverted_index.sedimentation | 379 |
| abstract_inverted_index.stratocumulus | 12 |
| abstract_inverted_index.understanding | 437 |
| abstract_inverted_index.100â<span | 241 |
| abstract_inverted_index.concentrations | 216 |
| abstract_inverted_index.stratocumulus. | 116 |
| abstract_inverted_index.1000â<span | 245 |
| abstract_inverted_index.recommendations | 424 |
| abstract_inverted_index.supersaturation | 251 |
| abstract_inverted_index.UCLALESâSALSA | 20, 93 |
| abstract_inverted_index.aerosolâcloud | 9 |
| abstract_inverted_index.well-characterized | 418 |
| abstract_inverted_index.radiation-dynamical | 113 |
| abstract_inverted_index.modelâsectional | 29 |
| abstract_inverted_index.turbulent-convective | 112 |
| abstract_inverted_index.sizeâcomposition | 74 |
| abstract_inverted_index.EcosystemâAtmosphere | 50 |
| abstract_inverted_index.coagulationâcoalescence. | 188 |
| abstract_inverted_index.class="inline-formula">cm<sup>â3</sup></span> | 242 |
| abstract_inverted_index.class="inline-formula">cm<sup>â3</sup></span>. | 246 |
| abstract_inverted_index.class="journal-contentHeaderColor">Abstract.</strong> | 1 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5034940507 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 1 |
| corresponding_institution_ids | https://openalex.org/I1285790362 |
| citation_normalized_percentile |