Aerosol-cloud interactions (ACI) are among the most complex and uncertain processes in climate science. Aerosols (tiny particles like sulfates, black carbon, dust, sea salt, or organics) influence cloud formation, microphysics, macrophysics, precipitation, and radiative properties. Clouds, in turn, can process and remove aerosols.

Core Mechanisms

1. Twomey Effect (First Indirect Effect / Cloud Albedo Effect)

Higher aerosol concentrations increase the number of cloud condensation nuclei (CCN). For a fixed liquid water content (LWC), this leads to:

• More but smaller cloud droplets.
• Increased cloud optical depth and albedo (brighter clouds that reflect more sunlight → cooling).

This is relatively well-understood and observable (e.g., ship tracks in marine stratocumulus).

2. Albrecht Effect (Second Indirect Effect / Cloud Lifetime Effect)

Smaller droplets reduce collision-coalescence efficiency, suppressing warm rain formation. This can:

• Increase cloud lifetime and liquid water path (LWP).
• Enhance cloud fraction and coverage.

Result: More persistent reflective clouds → additional cooling. This is modulated by meteorology (e.g., humidity, stability).

3. Aerosol Invigoration in Deep Convective Clouds

In mixed-phase or deep convective systems, aerosols can enhance vertical development:

• Smaller droplets are lofted higher before raining out.
• More supercooled water freezes at higher altitudes, releasing extra latent heat.
• This can strengthen updrafts, increase cloud-top height, anvil extent, and ice production.

Effects vary:

• Can lead to more intense precipitation in some cases or delayed/suppressed in others.
• Depends on aerosol type (e.g., pollution vs. smoke), loading, and environment (wind shear, humidity, stability).

Recent work (including Dagan 2026) highlights timescale dependence in convective regimes:

• Transient phase (~first 1–2 days after aerosol increase): Rapid microphysical invigoration boosts high-cloud (anvil) fraction → enhanced longwave trapping → positive ERF (warming).
• Equilibrium phase: Upper-tropospheric warming increases static stability, reducing anvil fraction → negative ERF (cooling) dominates.

The net effect depends on the ratio of adjustment timescale (τ_adj) to aerosol perturbation timescale (τ_aer). Rapid changes favor transient warming; gradual changes favor equilibrium cooling. Hysteresis can occur in intermediate regimes.

4. Semi-Direct Effect

Absorbing aerosols (e.g., black carbon) heat the atmosphere, which can:

• Increase stability and reduce cloud formation.
• Evaporate cloud droplets.

This often produces a warming (positive forcing) counteracting indirect cooling.

5. Ice-Phase and Mixed-Phase Effects

• Glaciation indirect effect: More ice-nucleating particles (INPs) can accelerate freezing of supercooled droplets, potentially enhancing precipitation efficiency via the ice phase.
• Riming indirect effect: Smaller droplets may reduce riming (ice collecting liquid), affecting snow/graupel formation.
• Thermodynamic effects: Delayed freezing allows clouds to reach colder temperatures.

6. Other Adjustments and Feedbacks

• Changes in cloud fraction, thickness, and coverage.
• Dynamical responses: Altered circulation, water vapor transport, or large-scale patterns. nature.com
• Meteorological modulation: Effects strengthen or reverse depending on updraft speed, lower-tropospheric stability (LTS), relative humidity, etc.

There is a new study from researchers at the Hebrew University of Jerusalem, led by Prof. Guy Dagan. It was published recently (around June 2026) in Nature Communications.

The study shows that aerosols (tiny atmospheric particles from pollution, wildfires, dust, sea spray, etc.) can have opposing effects on the climate depending on the timescale of their influence and how quickly their concentrations change. This challenges simpler assumptions about their net impact and helps explain why aerosol effects remain one of the biggest uncertainties in climate projections.

Dagan (2026) explores the time-dependent dynamics of aerosol-cloud interactions (ACI) in an idealized radiative-convective equilibrium (RCE) framework using high-resolution cloud-resolving simulations (System for Atmospheric Modeling – SAM).

It isolates local convective responses and environmental adjustments without large-scale circulation.

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Opposing transient and equilibrium effective radiative forcing from aerosol-cloud interactions

This is the title of a 2026 open-access paper by Guy Dagan (Hebrew University of Jerusalem) published in Nature Communications.

This idealized high-resolution modeling study isolates timescale-dependent mechanisms in deep convective regimes using the System for Atmospheric Modeling (SAM) in a radiative-convective equilibrium (RCE) framework. It avoids large-scale circulation complications to focus on local convective and environmental adjustments.

Experimental Setup

• Domain: Horizontally homogeneous, periodic, cloud-resolving grid (resolves deep convection; microphysics parameterized; limited shallow cloud resolution).
• Perturbations: Instantaneous jump in aerosol (CCN) from clean (~20 cm⁻³) to polluted (~2000 cm⁻³), plus ensemble runs from different initial states. Additional experiments with oscillating or gradually changing aerosol concentrations at prescribed periods (τ_aer).
• Key outputs: Time evolution of TOA net radiative flux (ΔR_net = ERF_ACI proxy), SW/LW components, cloud properties (LWP, IWP, cloud fraction), thermodynamic profiles, stability.

Transient Phase (~first 2 days): Positive ERF_ACI (Warming)

• Rapid microphysical invigoration: Higher CCN → more numerous/smaller droplets → delayed warm rain → more water lofted to freezing levels → enhanced latent heat release aloft → stronger updrafts.
• Macrophysical response: Increased high-cloud (anvil) fraction and ice water path (IWP). This enhances longwave trapping (reduced outgoing LW radiation, positive ΔR_LW peaking >40 W/m² transiently).
• Net effect: Positive transient ERF_ACI ≈ +9.4 W/m² (ensemble/time mean). Strong positive LW anomaly partially offset by negative SW (brighter/more reflective clouds via Twomey + LWP increase).

The initial shortwave response is negative (cooling) due to Twomey effect and LWP increase, but the LW warming dominates the net transient signal.

Equilibrium Phase (Longer-term steady state): Negative ERF_ACI (Cooling)

• Environmental adjustment: Upper-tropospheric warming from the transient invigoration increases static stability (reduced lapse rate).
• Feedback on clouds: Higher stability suppresses vertical development and reduces anvil cloud fraction/detrainment. This allows more LW escape to space (negative ΔR_LW).
• Net effect: Equilibrium ERF_ACI ≈ -6.8 W/m². Both SW and LW contribute negatively, with a weaker negative SW than in the transient phase.

Timescale Dependence and Hysteresis

he overall time-mean ERF_ACI depends on the ratio τ_adj / τ_aer:

• τ_adj (environmental adjustment timescale): ~days (upper-tropospheric warming and stability response).
• τ_aer (aerosol perturbation timescale): How fast concentrations change (e.g., sudden wildfire vs. gradual emissions).
• Rapid changes (τ_aer << τ_adj) → transient warming dominates.
• Slow/gradual changes (τ_aer >> τ_adj) → equilibrium cooling dominates.
• Intermediate regimes: Pronounced hysteresis — ERF_ACI depends on the history of aerosol loading, not just instantaneous value. Oscillating aerosol experiments demonstrate path dependence. nature.com

This explains why snapshot observations or models assuming quick equilibrium may misestimate forcing.

Broader Implications

• Reconciles conflicting signals: Helps explain variability in observed ACI; episodic events (wildfires, pollution spikes) may show short-term warming signatures, while sustained changes yield net cooling.
• Real-world relevance: Declining anthropogenic aerosols (air quality improvements) involve relatively rapid changes, potentially contributing to accelerated near-term warming by reducing the cooling mask and via transient dynamics.
• Modeling caveats: Idealized RCE (no large-scale circulation, SST fixed in core runs, parameterized microphysics). Builds on prior Dagan work on circulation adjustments and RCEMIP-ACI intercomparisons. Does not overturn the overall consensus of net negative global ERF_ACI but highlights strong timescale sensitivity in convective regimes.

This study elegantly demonstrates “atmospheric memory” in ACI: clouds and the environment retain a “memory” of recent aerosol history through thermodynamic adjustments.

It underscores the need for time-resolved approaches in observations, parameterizations, and projections—especially as aerosol emissions evolve rapidly compared to greenhouse gases.

For the full details, the open-access paper (with figures showing temporal evolutions) is available on Nature Communications.

Published: Nature Communications

DOI: 10.1038/s41467-026-72896-6

Method of Research: Computational simulation/modeling

Peer-Reviewed Publication

Author: Guy Dagan

Abstract

Aerosols influence clouds, and therefore Earth’s radiation budget, through processes that operate across multiple and interacting time scales, making aerosol-cloud interactions (ACI) a persistent source of uncertainty in estimates of effective radiative forcing (ERF).

Here we examine the time-dependent response of the local, convection-focused ERF_ACI using an ensemble of high-resolution simulations initialized from different atmospheric states and subjected to an instantaneous aerosol perturbation, together with simulations in which aerosol concentration changes with prescribed periods.

We find that the transient ERF_ACI during the first  ~ 2 days is positive, driven by rapid microphysical invigoration, enhanced high-cloud fraction, and increased longwave trapping.

In contrast, the equilibrium ERF_ACI becomes negative as upper-tropospheric warming increases static stability and reduces anvil cloud fraction.

As a result, the time-mean forcing depends on the ratio between the environmental adjustment time scale (τ_adj) and the aerosol-perturbation time scale (τ_aer).

For intermediate regimes, where τ_aer is only moderately longer than τ_adj, the system exhibits pronounced hysteresis: ERF_ACI depends not only on the instantaneous aerosol loading but also on its recent history.

These results imply that snapshot-based observational constraints and near-instantaneous-equilibrium convective parameterizations may systematically misestimate ERF_ACI.