Satellite-derived precipitation susceptibility has been widely used to constrain cloud water response to aerosols (the so-called cloud lifetime effects) and to study aerosol effects on precipitation. Recently, Bai et al. (2018) quantify the uncertainty in precipitation susceptibility on warm clouds over global oceans based on multi-sensor aerosol and cloud products from the A-Train satellites, including MODIS, AMSR-E, CALIOP and CLOUDSAT cloud radar observations, covering the period June 2006 to April 2011. In addition to different aerosol, cloud and rain products, we also analyze other factors that have potential influence on susceptibility, such as different definitions of precipitation susceptibility, stability regimes, and different thresholds for defining a rain event.
In general, precipitation frequency susceptibility (SPOP) is a relatively robust metric throughout different liquid water path (LWP) and rain products and its estimate is less sensitive to different datasets used. In contrast, precipitation intensity susceptibility (SI) differs considerably among different LWP and rain products. Precipitation susceptibility for drizzle (with -15 dBZ rainfall threshold) is significantly different from that for rain (with 0 dBZ rainfall threshold). Their results suggest that onset of drizzle is not as readily suppressed by increases in AI or CDNC in warm clouds as rainfall. This may partly come from the fact that precipitation frequency (POP) of drizzle is close to 100% at moderate and high LWP, which makes it insensitive to perturbations in droplet number concentration (CDNC) or aerosol index and results in smaller SPOP at these LWP bins compared with SPOP for rain. On the other hand, precipitation intensity susceptibility is generally smaller for rain than for drizzle. This is consistent with their expectation that when precipitation intensity increases, accretion contributes more to the production of precipitation, which makes precipitation intensity less sensitive to perturbation in CDNC, as accretion is less dependent on CDNC compared with autoconversion.
Figure 1 The LWP-weighed mean values of (a-b, e-f) SPOP and (c-d, g-h) SI under different stability regimes for four cases. The case1 and case2 are both based on 2B-GEOPROF product, but use threshold of -15 dBZ and 0 dBZ, respectively. The case3 and case4 use 2C-PRECIP-COLUMN and 2C-RAIN-PROFILE products, respectively. The top two panels use MODIS LWP and the bottom two panels use AMSR-E LWP. Error bars are based on the LWP-weighed mean values of 95% confidence intervals for the susceptibility estimates.
Bai, H., Gong, C., Wang, M. (*), Zhang, Z., and L'Ecuyer, T.: Estimating precipitation susceptibility in warm marine clouds using multi-sensor aerosol and cloud products from A-Train satellites, Atmos. Chem. Phys., 18, 1763-1783, https://doi.org/10.5194/acp-18-1763-2018, 2018.