Viime vuosien ja kuukausien lämpeneminen ei johdu ihmisestä

Pilvisyyden muodostus ja uusien pilviydinpartikkeleiden muodostus noudattelee fysiikan lakeja, niitä on kuitenkin mallinnuksia varten parametrisoitu, kun ei ole ollut esim. uusien partikkeleiden muodostumisista tietoa.

” New particle formation events persistently reduce cloud droplets in boundary layer clouds
David Patoulias et al. 
Α considerable fraction of cloud condensation nuclei (CCN) originates from new particle formation (NPF). Because of this, NPF events themselves are thought to also increase CCN and cloud droplet number (CDN) and contribute to climate cooling. High resolution state-of-the-art simulations over Europe however portray a different view: radiatively important stratiform clouds influenced by NPF events experience a systematic and substantial decrease in droplet number during and after nucleation events. The drop in CDN occurs because particles present prior to the NPF experiences slower growth during and after each event (as the condensable material is consumed by the growth of the NPF particles that do not typically activate), leading to fewer CCN at the low supersaturation levels characteristic of stratiform clouds (~0.1%). Convective clouds, however, tend to experience a modest increase in cloud droplet number – consistent with established views on the NPF-cloud link. Our results are corroborated by published observational evidence and all together reshape our conceptual understanding of NPF events on clouds, where droplets in stratiform clouds tend to be reduced (leading to local warming from reductions in cloud albedo) but enhance in convection. Combined, these effects could bear important impacts on cloud structure following NPF events.”

https://meetingorganizer.copernicus.org/EGU2020/EGU2020-13194.html

”Uudet hiukkasten muodostumistapahtumat vähentävät jatkuvasti pilvipisaroita rajakerrospilvissä

David Patoulias et al.
Huomattava osa pilvikondensaatioytimistä (CCN) on peräisin uusien hiukkasten muodostumisesta (NPF). Tämän vuoksi itse NPF-tapahtumien ajatellaan lisäävän CCN:n ja pilvien pisaroiden lukumäärää (CDN) ja edistävän ilmaston viilenemistä. Korkean resoluution huipputekniset simulaatiot Euroopassa kuvaavat kuitenkin erilaista näkemystä: säteilyllisesti tärkeät stratiformipilvet, joihin NPF-tapahtumat vaikuttavat, vaikuttavat systemaattisesti ja huomattavasti pisaroiden lukumäärään nukleaatiotapahtumien aikana ja niiden jälkeen. CDN:n lasku tapahtuu, koska ennen NPF:ää läsnä olevat hiukkaset kasvavat hitaammin kunkin tapahtuman aikana ja sen jälkeen (koska tiivistyvä materiaali hupenee NPF-hiukkasten kasvuun, jotka tyypillisesti eivät aktivoidu), mikä johtaa CCN:n vähentymiseen alhaisilla ylikyllästymisasteilla, kuten on kerrospilvien ominaispiirteenä (~ 0,1%). Konvektiivisilla pilvillä on kuitenkin taipumus kokea kohtuullinen pilvipisaroiden lukumäärän kasvu – sopusoinnussa NPF-pilvi-linkin vakiintuneiden näkymien kanssa. Tuloksia vahvistavat julkaistut havainnot ja ne kaikki muuttavat käsitteellistä käsitystämme NPF-tapahtumista pilvissä, joissa stratiformipilvien pisarat yleensä vähenevät (johtaen paikallisiin lämpenemisiin pilvialbeedon vähenemisestä), mutta parantavat konvektiota. Yhdessä nämä vaikutukset voivat aiheuttaa merkittäviä vaikutuksia pilvirakenteeseen NPF-tapahtumien jälkeen.”

https://meetingorganizer.copernicus.org/EGU2020/EGU2020-13194.html

”Xiang-Yu Li et al.
Xiang-Yu Li et al. Received: 27 Jun 2018 – Discussion started: 28 Aug 2018 – Revised: 13 Dec 2018 – Accepted: 15 Dec 2018 – Published: 17 Jan 2019
Abstract 
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Condensational growth of cloud droplets due to supersaturation fluctuations is investigated by solving the hydrodynamic and thermodynamic equations using direct numerical simulations (DNS) with droplets being modeled as Lagrangian particles. The supersaturation field is calculated directly by simulating the temperature and water vapor fields instead of being treated as a passive scalar. Thermodynamic feedbacks to the fields due to condensation are also included for completeness. We find that the width of droplet size distributions increases with time, which is contrary to the classical theory without supersaturation fluctuations, where condensational growth leads to progressively narrower size distributions. Nevertheless, in agreement with earlier Lagrangian stochastic models of the condensational growth, the standard deviation of the surface area of droplets increases as t1∕2. Also, for the first time, we explicitly demonstrate that the time evolution of the size distribution is sensitive to the Reynolds number, but insensitive to the mean energy dissipation rate. This is shown to be due to the fact that temperature fluctuations and water vapor mixing ratio fluctuations increase with increasing Reynolds number; therefore the resulting supersaturation fluctuations are enhanced with increasing Reynolds number. Our simulations may explain the broadening of the size distribution in stratiform clouds qualitatively, where the mean updraft velocity is almost zero.
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1 Introduction 
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The growth of cloud droplets is dominated by two processes: condensation and collection. Condensation of water vapor on active cloud condensation nuclei is important in the size range from the activation size of aerosol particles to about a radius of 10µm (Lamb and Verlinde, 2011; Pruppacher and Klett, 2012). Since the rate of droplet growth by condensation is inversely proportional to the droplet radius, large droplets grow slower than smaller ones. This generates narrower size distributions (Lamb and Verlinde, 2011). To form rain droplets in warm clouds, small droplets must grow to about 50µm in radius within 15–20 min (Devenish et al., 2012; Grabowski and Wang, 2013; Pruppacher and Klett, 2012; Seinfeld and Pandis, 2016). Therefore, collection, a widely accepted microscopical mechanism, has been proposed to explain the rapid formation of rain droplets (Berry and Reinhardt, 1974; Grabowski and Wang, 2013; Saffman and Turner, 1956; Shaw, 2003). However, collection can only become active when the size distribution reaches a certain width.
Hudson and Svensson (1995) observed a broadening of the droplet size distribution in Californian marine stratus, which was contrary to the classical theory of condensational growth (Yau and Rogers, 1996). The increasing width of droplet size distributions was further observed by Pawlowska et al. (2006) and Siebert and Shaw (2017). The contradiction between the observed broadening width and the theoretical narrowing width in the absence of turbulence has stimulated several studies. The classical treatment of diffusion-limited growth assumes that supersaturation depends only on average temperature and water mixing ratio. Since fluctuations of temperature and the water mixing ratio are affected by turbulence, the supersaturation fluctuations are inevitably subjected to turbulence. Naturally, condensational growth due to supersaturation fluctuations became the focus (Cooper, 1989; Grabowski and Abade, 2017; Kabanov and Mazin, 1970; Khvorostyanov and Curry, 1999; Korolev, 1995; Sardina et al., 2015; Sedunov, 1965; Srivastava, 1989). The supersaturation fluctuations are particularly important for understanding the condensational growth of cloud droplets in stratiform clouds, where the updraft velocity of the parcel is almost zero (Hudson and Svensson, 1995; Korolev, 1995). When the mean updraft velocity is not zero, there could be a competition between mean updraft velocity and supersaturation fluctuations. This may diminish the role of supersaturation fluctuations (Sardina et al., 2018).
Condensational growth due to supersaturation fluctuations was first recognized by Srivastava (1989), who criticized the use of a volume-averaged supersaturation and proposed a randomly distributed supersaturation field. Cooper (1989) proposed that droplets moving in clouds are exposed to a varying supersaturation field. This results in a broadening of the droplet size distribution due to supersaturation fluctuations. Grabowski and Wang (2013) called the mechanism of Cooper (1989) the eddy-hopping mechanism, which was then investigated by Grabowski and Abade (2017). Using direct numerical simulations (DNS), Vaillancourt et al. (2002) found that the mean energy dissipation rate of turbulence has a negligible effect on condensational growth and attributed this to the decorrelation between the supersaturation and the droplet size. Paoli and Shariff (2009) considered three-dimensional (3-D) turbulence as well as stochastically forced temperature and vapor fields with a focus on statistical modeling for large-eddy simulations. They found that supersaturation fluctuations due to turbulence mixing are responsible for the broadening of the droplet size distribution. Lanotte et al. (2009) conducted 3-D DNS for condensational growth by only solving a passive scalar equation for the supersaturation and concluded that the width of the size distribution increases with increasing Reynolds number. Sardina et al. (2015) extended the DNS of Lanotte et al. (2009) to a higher Reynolds number and found that the variance of the size distribution increases in time. In a similar manner as Sardina et al. (2015), Siewert et al. (2017) modeled the supersaturation field as a passive scalar coupled to the Lagrangian particles and found that their results can be reconciled with those of earlier numerical studies by noting that the droplet size distribution broadens with increasing Reynolds number (Lanotte et al., 2009; Paoli and Shariff, 2009; Sardina et al., 2015). Neither Sardina et al. (2015) nor Siewert et al. (2017) solved the thermodynamics that determine the supersaturation field. Both Saito and Gotoh (2017) and Chen et al. (2018) solved the thermodynamics equations governing the supersaturation field. However, since collection was also included in their work, one cannot clearly identify the roles of turbulence on collection or condensational growth, nor can one compare their results with Lagrangian stochastic models (Sardina et al., 2015; Siewert et al., 2017) related to condensational growth.
Recent laboratory experiments and observations about cloud microphysics also confirm the notion that supersaturation fluctuations may play an important role in broadening the size distribution of cloud droplets. The laboratory studies of Chandrakar et al. (2016) and Desai et al. (2018) suggested that supersaturation fluctuations in the low aerosol number concentration limit are likely of leading importance for the onset of precipitation. The condensational growth due to supersaturation fluctuations seems to be more sensitive to the integral scale of turbulence (Götzfried et al., 2017). Siebert and Shaw (2017) measured the variability of temperature, water vapor mixing ratio, and supersaturation in warm clouds and support the notion that both aerosol particle activation and droplet growth take place in the presence of a broad distribution of supersaturation (Brenguier et al., 1998; Hudson and Svensson, 1995; Miles et al., 2000; Pawlowska et al., 2006). The challenge is now how to interpret the observed broadening of the droplet size distribution in warm clouds. How does turbulence drive fluctuations of the scalar fields (temperature and water vapor mixing ratio) and therefore affect the broadening of droplet size distributions (Siebert and Shaw, 2017)?”

https://www.atmos-chem-phys.net/19/639/2019/

”Chandrakar et al. (2016) ja Desai et al. (2018) ehdotti, että ylikyllästymisvaihteluilla alhaisessa aerosolipitoisuusrajassa on todennäköisesti keskeinen merkitys sateiden alkamiselle. Ylikyllästymisvaihteluista johtuva tiivistyvä kasvu näyttää olevan herkempi turbulenssin integroidulle asteikolle (Götzfried ym., 2017). Siebert ja Shaw (2017) mittasivat lämpötilan, vesihöyryn sekoitussuhteen ja ylikyllästymisen vaihtelua lämpimissä pilvissä ja tukevat ajatusta, että sekä aerosolihiukkasten aktivoituminen että pisaroiden kasvu tapahtuvat, kun ylikyllästyminen jakautuu laajasti (Brenguier et al. , 1998; Hudson ja Svensson, 1995; Miles et al., 2000; Pawlowska et al., 2006). Haasteena on nyt, miten tulkita lämpimissä pilvissä havaittua pisarakoon jakautumista. Kuinka turbulenssi ajaa skalaarikenttien (lämpötilan ja vesihöyryn sekoitussuhteen) vaihteluita ja vaikuttaa siten pisaroiden kokojakauman laajenemiseen (Siebert ja Shaw, 2017)?”