Estimating cloud concentration nuclei number concentrations using aerosol optical properties: role of particle number size distribution and parameterization

• Main Authors: Y. Shen, A. Virkkula, A. Ding, K. Luoma, H. Keskinen, P. P. Aalto, X. Chi, X. Qi, W. Nie, X. Huang, T. Petäjä, M. Kulmala, V.-M. Kerminen
• Format: Article
• Language: English
• Published: Copernicus Publications 2019-12-01
• Series: Atmospheric Chemistry and Physics
• Online Access: https://www.atmos-chem-phys.net/19/15483/2019/acp-19-15483-2019.pdf
• ISSN: 1680-7316; 1680-7324

<p>The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol–cloud interactions within warm clouds. Long-term CCN number concentration (<span class="inline-formula"><i>N</i>_CCN</span>) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating <span class="inline-formula"><i>N</i>_CCN</span> from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between <span class="inline-formula"><i>N</i>_CCN</span>, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Ångström exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (<span class="inline-formula"><i>σ</i>_sp</span>) of PM<span class="inline-formula">₁₀</span> particles. The analysis first showed that the dependence of <span class="inline-formula"><i>N</i>_CCN</span> on supersaturation (SS) can be described by a logarithmic fit in the range SS&thinsp;<span class="inline-formula">&lt;1.1</span>&thinsp;%, without any theoretical reasoning. The relationship between <span class="inline-formula"><i>N</i>_CCN</span> and AOPs was parameterized as <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M9" display="inline" overflow="scroll" dspmath="mathml"><mrow><msub><mi>N</mi><mi mathvariant="normal">CCN</mi></msub><mo>≈</mo><mo>(</mo><mo>(</mo><mn mathvariant="normal">286</mn><mo>±</mo><mn mathvariant="normal">46</mn><mo>)</mo></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="93pt" height="13pt" class="svg-formula" dspmath="mathimg" md5hash="1db18230eee7b12e7ed258c4199f0c7d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-15483-2019-ie00001.svg" width="93pt" height="13pt" src="acp-19-15483-2019-ie00001.png"/></svg:svg></span></span>SAE ln(SS/(<span class="inline-formula">0.093±0.006</span>))(BSF <span class="inline-formula">−</span> BSF<span class="inline-formula">_min</span>) <span class="inline-formula">+</span> (<span class="inline-formula">5.2±3.3</span>))<span class="inline-formula"><i>σ</i>_sp</span>, where BSF<span class="inline-formula">_min</span> is the minimum BSF, in practice the 1st percentile of BSF data at a site to be analyzed. At the lowest supersaturations of each site (SS&thinsp;<span class="inline-formula">≈0.1</span>&thinsp;%), the average bias, defined as the ratio of the AOP-derived and measured <span class="inline-formula"><i>N</i>_CCN</span>, varied from <span class="inline-formula">∼0.7</span> to <span class="inline-formula">∼1.9</span> at most sites except at a Himalayan site where the bias was <span class="inline-formula">&gt;4</span>. At SS&thinsp;<span class="inline-formula">&gt;0.4</span>&thinsp;% the average bias ranged from <span class="inline-formula">∼0.7</span> to <span class="inline-formula">∼1.3</span> at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, <span class="inline-formula">∼1.4</span>–1.9. In other words, at SS&thinsp;<span class="inline-formula">&gt;0.4</span>&thinsp;% <span class="inline-formula"><i>N</i>_CCN</span> was estimated with an average uncertainty of approximately 30&thinsp;% by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Ångström exponent (SAE). The squared correlation coefficients between the AOP-derived and measured <span class="inline-formula"><i>N</i>_CCN</span> varied from <span class="inline-formula">∼0.5</span> to <span class="inline-formula">∼0.8</span>. To study the physical explanation of the relationships between <span class="inline-formula"><i>N</i>_CCN</span> and AOPs, lognormal unimodal particle size distributions were generated and <span class="inline-formula"><i>N</i>_CCN</span> and AOPs were calculated. The simulation showed that the relationships of <span class="inline-formula"><i>N</i>_CCN</span> and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of <span class="inline-formula"><i>N</i>_CCN</span> and AOPs were similar to those of the observed ones.</p>