Marine Cloud Brightening (MCB)

Marine Cloud Brightening - the benefits and options

MCB could be more limited in its effectiveness to influence the global mean temperatures but it can have other positive impacts for the Earth's climate, as leading to regional temperature effects (Kravitz et al., 2013) and may partially offset certain impacts of climate change, such as extreme weather events, prolonged droughts, and heatwaves. However, substantial uncertainties remain regarding its climatic effectiveness and possible adverse regional impacts—including pronounced cooling in high-latitude regions, overcooling of the tropics, residual warming at mid–high latitudes, and modifications to regional precipitation patterns (Stjern et al., 2018).

For MCB studies, the most effective material proposed to feed the marine clouds is the Sea Salt particles (Hernandez-Jaramillo et al., 2023), even though other materials like smoke particles and sodium chloride (salt) particles have been proposed to the literature too. The most widely known technology to persistently feed clouds with appropriate aerosols at the Planetary Boundary Level (PBL) is via using engineering Spray Nozzles (Hernandez-Jaramillo et al., 2023). Efficiency depends on meteorological conditions, aerosol size distribution, humidity, and thermodynamic instability. Key uncertainties remain regarding optimal particle properties, meteorological targeting, side effects, and detectability. Currently the uncertainties in Spray Parameters and Delivery Strategy are huge as there is limited understanding of the optimal droplet size, spray flux, nozzle design, and marine location for MCB. The effectiveness of cloud brightening depends on background cloud properties (LWP, CCN), updraft conditions, and aerosol-cloud interactions that are poorly constrained. Variability in outcome across modeling studies is large. The effects of timing and rate of marine cloud brightening aerosol injection on albedo changes are examined during the diurnal cycle of marine stratocumulus clouds (Jenkins et al., 2013).

Cloud-Aerosol Interactions are very complex and not well understood yet. Enhancing cloud albedo through increased cloud droplet number concentration (CDNC) is non-linear and sensitive to cloud regime (e.g., stratocumulus vs. trade cumulus). Feedbacks such as cloud thinning, precipitation suppression, or evaporative invigoration create response diversity (Quaas et al., 2009; Diamond et al., 2020). There are understudied environmental and climatic side effects as MCB may disrupt precipitation patterns or alter heat fluxes and circulation (Kravitz et al., 2013; Stjern et al., 2018).

Most climate models simplify marine low cloud processes, often lacking explicit cloud microphysics or resolving mesoscale organization. Cloud feedbacks and aerosol indirect effects in MCB scenarios remain uncertain, as revealed by GeoMIP and MCB-specific modeling studies. The models does not fully capture cloud dynamics, aerosol dispersion, or feedbacks in the real Earth system, limiting confidence in the spatial precision of predicted impacts (Jones et al., 2009).

Technological Feasibility and Operational Control: No scalable and controllable spray technology exists. Prototypes for sea-salt particle generation or/and marine vessel delivery remain in the experimental phase, with concerns about energy requirements, particle dispersion, and operational safety. An initial analysis of the energy budget needed for MCB would imply that the intervention is translated into energy needs. MCB would require the sustained generation and dispersion of large quantities of submicron sea-salt particles over extensive ocean regions in order to measurably enhance cloud albedo. Although conceptual studies suggest that such interventions could modify cloud reflectivity under favorable meteorological conditions, the total mass flux of particles required, the number of deployment platforms, and the spatial coverage necessary to achieve climatically significant forcing remain highly uncertain. Consequently, the associated energy demand, operational logistics, technological scalability, and long-term economic implications of continuous aerosol generation and delivery are not yet well quantified.

Detectability and Attribution Challenges: Because MCB effects are expected to be subtle and localized, distinguishing them from natural variability and anthropogenic aerosol signals is difficult. Detecting changes in cloud albedo, microphysical properties, or radiative forcing requires high-resolution, long-term EO datasets and robust attribution frameworks (Bender et al., 2016).

Key knowledge gaps addressed by ACtIon4Cooling

ACtIon4Cooling addressed key knowledge gaps related to MCB through observational analysis of natural and anthropogenic analogues such as ship tracks. The project focused on:

• Identifying regions where marine low clouds exhibit high susceptibility to aerosol perturbations.
• Quantifying associated radiative and precipitation responses at regional and global scales.
• Monitoring changes in cloud microphysics and top-of-atmosphere radiative properties using Earth Observation data.
• Providing empirical constraints to improve aerosol–cloud interaction parameterizations in climate models.
• Developing methodologies to distinguish MCB-like signals from natural variability and broader anthropogenic aerosol effects.

The ACtIon4Cooling project investigates observable cloud perturbations associated with ship emissions as a real-world analogue for Marine Cloud Brightening (MCB). Rather than evaluating deployment effectiveness at global scale, the project quantifies measurable cloud responses to existing ship-induced aerosol perturbations at regional scale, focusing on the Mediterranean Sea and the North-East Atlantic.

Marine clouds co-located with ship-track signatures are analyzed to identify changes in cloud cover, reflectivity, and microphysical properties relative to surrounding background cloud fields. Daily regional perturbation statistics are derived by comparing the mean of ship-affected pixels with the mean of background pixels within the same day and grid box, enabling both pixel-level and aggregated assessments of ship-induced cloud modifications.

Marine cloud properties are retrieved from the spaceborne Ultraviolet Visible Near-infrared (UVN) spectrometer TROPOMI aboard Sentinel-5 Precursor (Veefkind et al., 2012). The TROPOMI operational algorithms for the retrieval of cloud parameters (Loyola et al., 2018) make use of Earth-shine reflectance measurements in the spectral windows of UV, VIS and NIR. Complementary information for marine clouds is exploited from the VIIRS instrument on Suomi NPP, providing cloud microphysical properties such as effective radius and liquid water path.

Aerosol information relevant to ship emissions is derived from TROPOMI measurements in the oxygen absorption bands (e.g., aerosol layer height) and in the UV spectral window. In particular, the ultraviolet (UV) Absorbing Aerosol Index (AAI) is widely used as an indicator for the presence of absorbing aerosols in the atmosphere (Kooreman et al., 2020; Torres et al., 1998a). The ship-track aerosol signature is further investigated using the scientific NASA TropOMAER (TROPOMI aerosol algorithm), which simultaneously retrieves aerosol optical depth (AOD), single-scattering albedo (SSA), and the qualitative UV aerosol index (UVAI) (Torres et al., 2020).

In addition, tropospheric nitrogen dioxide (NO₂) vertical column densities retrieved from TROPOMI are used as an independent tracer of combustion-related ship emissions. The co-location of enhanced NO₂ columns with aerosol and cloud perturbations strengthens the attribution of observed cloud modifications to ship activity.

This observational framework enables a data-driven assessment of ship-induced cloud perturbations and provides quantitative constraints relevant for understanding aerosol–cloud interactions in the context of marine cloud brightening research.

Summary & Results

For MCB the vessel density maps from the European Marine Observation and Data Network (EMODnet) were used for defining where the ships are located. The primary information on cloud properties was acquired from Sentinel-5 Precursor/TROPOMI. Complementary information for the clouds captured by TROPOMI instrument was taken from VIIRS on Suomi-NPP. The TROPOMI NO₂ Tropospheric Vertical Column Densities (VCDs) were analyzed to quantify shipping-related nitrogen dioxide enhancements along major maritime corridors in the Mediterranean Sea and North Eastern Atlantic.

The shipping emissions can be systematically detected in the NO₂ Tropospheric column. The sign of the perturbation is always positive; the magnitude of the NO₂ perturbation is large (~30% for the Mediterranean region). On the contrary, the perturbations of the cloud parameters may change sign from day to day. The natural variability of the clouds masks the signal of the modification due to the ship-emitted particles at their cloud base.

Therefore, the automatic ship-track detection in all conditions could be challenging with the use of Machine Learning (ML) techniques. The primary goal is to develop a ship-track detection model accurate enough to enable the estimation of local pixel-by-pixel cloud perturbations, computed as the difference between ship-affected pixels and background reference pixels within the same scene and meteorological regime. The latter is only possible with densely populated ship-relevant datasets which could be used for the training of a ML classifier. Until that trustworthy ship-track detection model is built, the most robust way to quantify cloud perturbations due to ships is the regional mean perturbation formula (i.e., the difference of the mean of ship-affected pixels per day and grid box minus the mean of background pixels per day and grid box).

The regional daily perturbation dataset (ship-mean versus background-mean approach) is more directly aligned with policy-relevant detectability questions. By aggregating signals at regional and daily scales, it reflects how monitoring systems for SRM would likely be operationalized in practice. This approach enables statistical robustness and provides a bridge between process-level understanding and operational climate intervention monitoring strategies.

The satellite-observed ship-affected marine cloud perturbations were reproduced in the ICON simulation to evaluate the global impacts of MCB. Pairs of global simulations were performed for attribution of effects, with and without the observations-based cloud perturbation. In the perturbed simulation, the liquid water path was increased by 1%, as suggested by observations over the region of interest. For the observations-derived perturbation of a mere 1%, no clear perturbation to the top-of-atmosphere radiation budget or surface air temperature is detected within the region of interest suggesting that the imposed perturbation is masked by signals arising from cloud adjustments. In turn, for a strong perturbation of a factor of 10, a regional effective radiative forcing of 15 Wm^-2 was obtained, with little perturbation to the top-of-atmosphere radiation budget outside the region of interest.

In consequence, there is no discernible perturbation of temperatures in the observations-tied perturbation. For the strong perturbation, in turn, surface air temperature increased locally by up to 0.5K, suggesting the relevance of Earth system feedbacks for the analysis of MCB climate effects. Precipitation responses extend beyond the region of imposed perturbation, reflecting the strong coupling between latent heating, large-scale circulation, and atmospheric energy balance. A similar spatial pattern of precipitation response is obtained for the strong and the weak perturbation simulations. This suggests that the precipitation changes are instead dominated by internal variability and rapid adjustment processes.

References

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