Predicting decadal trends in cloud droplet number concentration using reanalysis and satellite data

Abstract

Abstract. Cloud droplet number concentration (CDNC) is the key state variable that moderates the relationship between aerosol and the radiative forcing arising from aerosolcloud interactions. Uncertainty related to the effect of anthropogenic aerosol on cloud properties represents the largest uncertainty in total anthropogenic radiative forcing. Here we show that regionally averaged time series of the ModerateResolution Imaging Spectroradiometer (MODIS) observed CDNC of low, liquid-topped clouds is well predicted by the MERRA2 reanalysis near-surface sulfate mass concentration over decadal timescales. A multiple linear regression between MERRA2 reanalyses masses of sulfate (SO 4 ), black carbon (BC), organic carbon (OC), sea salt (SS), and dust (DU) shows that CDNC across many different regimes can be reproduced by a simple power-law fit to near-surface SO 4 , with smaller contributions from BC, OC, SS, and DU. This confirms previous work using a less sophisticated retrieval of CDNC on monthly timescales. The analysis is supported by an examination of remotely sensed sulfur dioxide (SO 2 ) over maritime volcanoes and the east coasts of North America and Asia, revealing that maritime CDNC responds to changes in SO 2 as observed by the ozone monitoring instrument (OMI). This investigation of aerosol reanalysis and top-down remote-sensing observations reveals that emission controls in Asia and North America have decreased CDNC in their maritime outflow on a decadal timescale.

Synergetic Satellite Trend Analysis of Aerosol and Warm Cloud Properties ver Ocean and Its Implication for Aerosol‐Cloud Interactions

“…(Figures 3 and S3-S5). For EUS and WEU regions, negative trends in CDNC and AOD are consistent with previous studies (Bennartz & Rausch, 2017;Li et al, 2018;Mao et al, 2014;Pozzer et al, 2015;Yoon et al, 2014;Zhao et al, 2017) and are closely related to a persistent decline in air pollutant emissions in the eastern United States and Western Europe (Krotkov et al, 2016;McCoy et al, 2018;Pozzer et al, 2015;Xing et al, 2013;Zhao et al, 2017). For annual time series of aerosol properties over EC (Figure 3 study areas between the present work and previous studies.…”

Aerosol midlatitude cyclone indirect effects in observations and high-resolution simulations

“…These have shown consistency between MODIS CDNC and sulfate mass from MERRA2 as well as observations of boundary-layer sulfur dioxide from the Ozone Monitoring Instrument (OMI) (McCoy et al, 2018).…”

“…Previous studies have shown that MERRA2 sulfate mass is a good predictor of CDNC as retrieved by MODIS (McCoy et al, , 2018. The relationship used in the present study to calculate CDNC from 910 hPa sulfate mass is CDNC = 10 0.41log 10 SO 4 +2.1 , where CDNC is in units of cm −3 and SO4 is in units of µg m −3 .…”

“…Retrievals of CDNC from the MODIS instrument were performed as described in Grosvenor and Wood (2014) and are the same data evaluated in McCoy et al (2018). In the present study, Level-2 swath data (joint product) from MODIS collection 5.1 (King et al, 2003) are filtered by removing pixels with solar zenith angles (SZAs) greater than 65 • to eliminate problematic retrievals at a pixel level (Grosvenor and Wood, 2014).…”

“…To avoid these ambiguities we take a similar approach to previous studies (Boucher and Lohmann, 1995) and use both CDNC retrieved by MODIS and the sulfate mass concentration at the surface simulated by MERRA2 reanalysis (McCoy et al, , 2018. This use of the sulfate mass as a proxy for MODIS observations of CDNC is advantageous because it is not susceptible to retrieval error and because MERRA2 does not have a parameterized cloud-aerosol indirect effect.…”