An emulator approach to stratocumulus susceptibility

• Main Authors: F. Glassmeier, F. Hoffmann, J. S. Johnson, T. Yamaguchi, K. S. Carslaw, G. Feingold
• Format: Article
• Language: English
• Published: Copernicus Publications 2019-08-01
• Series: Atmospheric Chemistry and Physics
• Online Access: https://www.atmos-chem-phys.net/19/10191/2019/acp-19-10191-2019.pdf

<p>The climatic relevance of aerosol–cloud interactions depends on the sensitivity of the radiative effect of clouds to cloud droplet number <span class="inline-formula"><i>N</i></span>, and liquid water path LWP. We derive the dependence of cloud fraction CF, cloud albedo <span class="inline-formula"><i>A</i>_C</span>, and the relative cloud radiative effect <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mrow><mtext>rCRE</mtext><mo>=</mo><mtext>CF</mtext><mo>⋅</mo><msub><mi>A</mi><mtext>C</mtext></msub></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="75pt" height="13pt" class="svg-formula" dspmath="mathimg" md5hash="04b90a5dc217adf737c6571084a1e32c"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-10191-2019-ie00001.svg" width="75pt" height="13pt" src="acp-19-10191-2019-ie00001.png"/></svg:svg></span></span> on <span class="inline-formula"><i>N</i></span> and LWP from 159 large-eddy simulations of nocturnal stratocumulus. These simulations vary in their initial conditions for temperature, moisture, boundary-layer height, and aerosol concentration but share boundary conditions for surface fluxes and subsidence. Our approach is based on Gaussian-process emulation, a statistical technique related to machine learning. We succeed in building emulators that accurately predict simulated values of CF, <span class="inline-formula"><i>A</i>_C</span>, and rCRE for given values of <span class="inline-formula"><i>N</i></span> and LWP. Emulator-derived susceptibilities <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M7" display="inline" overflow="scroll" dspmath="mathml"><mrow><mo>∂</mo><mi>ln⁡</mi><mtext>rCRE</mtext><mo>/</mo><mo>∂</mo><mi>ln⁡</mi><mi>N</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="79pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="754867febeb12f3e2702559dae288dbe"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-10191-2019-ie00002.svg" width="79pt" height="14pt" src="acp-19-10191-2019-ie00002.png"/></svg:svg></span></span> and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M8" display="inline" overflow="scroll" dspmath="mathml"><mrow><mo>∂</mo><mi>ln⁡</mi><mtext>rCRE</mtext><mo>/</mo><mo>∂</mo><mi>ln⁡</mi><mtext>LWP</mtext></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="94pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="13d5a44c4b9d759c1e81a57e52a37726"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-10191-2019-ie00003.svg" width="94pt" height="14pt" src="acp-19-10191-2019-ie00003.png"/></svg:svg></span></span> cover the nondrizzling, fully overcast regime as well as the drizzling regime with broken cloud cover. Theoretical results, which are limited to the nondrizzling regime, are reproduced. The susceptibility <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M9" display="inline" overflow="scroll" dspmath="mathml"><mrow><mo>∂</mo><mi>ln⁡</mi><mtext>rCRE</mtext><mo>/</mo><mo>∂</mo><mi>ln⁡</mi><mi>N</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="79pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="febfb39e1021efe691810f564824a15b"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-10191-2019-ie00004.svg" width="79pt" height="14pt" src="acp-19-10191-2019-ie00004.png"/></svg:svg></span></span> captures the strong sensitivity of the cloud radiative effect to cloud fraction, while the susceptibility <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mrow><mo>∂</mo><mi>ln⁡</mi><mtext>rCRE</mtext><mo>/</mo><mo>∂</mo><mi>ln⁡</mi><mtext>LWP</mtext></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="94pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="9db89e2bed541b688ed7a46d4da6c12d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-10191-2019-ie00005.svg" width="94pt" height="14pt" src="acp-19-10191-2019-ie00005.png"/></svg:svg></span></span> describes the influence of cloud amount on cloud albedo irrespective of cloud fraction. Our emulation-based approach provides a powerful tool for summarizing complex data in a simple framework that captures the sensitivities of cloud-field properties over a wide range of states.</p>