Decomposing Effective Radiative Forcing due to Aerosol Cloud Interactions by Global Cloud Regimes

Abstract

The radiative forcing (RF) produced by aerosol remains a large source of uncertainty in climate models (IPCC, 2013). General Circulation Models (GCMs) show a wide range in their predictions of aerosol forcing, through the uncertainty in effective radiative forcing, due to aerosol-cloud interactions ( et al., 2020).Aerosol-cloud interactions are driven by a number of different effects, occurring on different timescales. Instantaneous effects will drive changes in the instantaneous radiative forcing due to aerosol-cloud interactions (RF ACI ). For instance, the Twomey effect predicts that a cloud with constant liquid water content will increase in optical depth when aerosol loading increases (Twomey, 1977). Effects that occur over longer timescales will instead affect the ERF ACI , for instance the 2nd indirect effect (Albrecht, 1989) predicts that aerosol leads to increased liquid water path and cloud lifetime (Rotstayn, 1999). These effects are difficult to constrain however, due to the need for parameterization in GCMs owing to the microscopic nature of aerosol-cloud interactions, the huge heterogeneity in aerosol loading, and the uncertainty in the exact nature of these mechanisms themselves (Boucher et al., 2013).Even within GCMs, the indirect forcing by aerosol can vary wildly. As can be seen in Mulcahy et al. (2018), the change in forcing due to aerosol-cloud interactions (ERF ACI ) between the GA7.0 and GA7.1 (Global Atmosphere) science configurations of HadGEM3 (Hadley Center Global Environmental Model version 3) was 1.04 Wm −2 . As a result, it remains a question as to exactly why these changes can bring about such large variation in ERF ACI , and which types of cloud are the most sensitive to these changes in the model. One way to do this is to examine the ERF ACI when it is decomposed into cloud regimes. This will also give a detailed

Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing

“…We evaluate the potential of several types of observations, related to clouds and aerosol-cloud interactions in multiple locations and times of the year, to serve as global mean ΔFaer constraints and refer to them collectively as 'constraint variables'. We use satellite-derived observations over 5 regions of persistent stratocumulus cloud (Methods) known to be key regions for interrogating processes that affect aerosol-cloud interactions (31,32). To find a set of useful constraint variables (i.e.…”

Supplementary material to "Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing"

“…S26). These regions are dominated by stratocumulus cloud, have relatively high multi-model diversity in cloud amount in CMIP6 models (43) and are the most important regions for understanding the role of aerosol-cloud interactions (44). We only used values corresponding to model grid boxes with at least 50% ocean coverage in our area-weighted regional mean calculations.…”