Dr Adam Povey FRMetSoc FHEA

Abstract:

Uncertainty-bounded satellite retrievals of volcanic ash cloud properties such as ash cloud-top height, effective radius, optical depth and mass loading are needed for the robust quantitative assessment required to warn aviation of potential hazards. Moreover, there is an imperative to improve quantitative ash cloud estimation due to the planned move towards quantitative ash concentration forecasts by the Volcanic Ash Advisory Centers. Here we apply the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm to Advanced Himawari Imager (AHI) measurements of the ash clouds produced by the June 2019 Raikoke (Russia) eruption. The ORAC algorithm uses an optimal estimation technique to consolidate a priori information, satellite measurements and associated uncertainties into uncertainty-bounded estimates of the desired state variables. Using ORAC, we demonstrate several improvements in thermal infrared volcanic ash retrievals applied to broadband imagers. These include an improved treatment of measurement noise, accounting for multi-layer cloud scenarios, distinguishing between heights in the troposphere and stratosphere, and the retrieval of a wider range of effective radii sizes than existing techniques by exploiting information from the 10.4 µm channel. Our results indicate that 0.73 ± 0.40 Tg of very fine ash (radius ≤ 15 µm) was injected into the atmosphere during the main eruptive period from 21 June 18:00 UTC to 22 June 10:00 UTC. The total mass of very fine ash decreased from 0.73 to 0.10 Tg over ∼ 48 h, with an e-folding time of 20 h. We estimate a distal fine ash mass fraction of 0.73 % ± 0.62 % based on the total mass of very fine ash retrieved and the ORAC-derived height–time series. Several distinct ash layers were revealed by the ORAC height retrievals. Generally, ash in the troposphere was composed of larger particles than ash present in the stratosphere. We also find that median ash cloud concentrations fall below peak ash concentration safety limits (< 4 mg m−3) 11–16 h after the eruption begins, if typical ash cloud geometric thicknesses are assumed. The ORAC height retrievals for the near-source plume showed good agreement with GOES-17 side-view height data (R=0.84; bias = −0.75 km); however, a larger negative bias was found when comparing ORAC height retrievals for distal ash clouds against Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP) measurements (R=0.67; bias = −2.67 km). The dataset generated here provides uncertainties at the pixel level for all retrieved variables and could potentially be used for dispersion model validation or be implemented in data assimilation schemes. Future work should focus on improving ash detection, improving height estimation in the stratosphere and exploring the added benefit of visible channels for retrieving effective radius and optical depth in opaque regions of nascent ash plumes.

Abstract:

Estimates of the anthropogenic effective radiative forcing (ERF) trend have increased by 50% since 2000 (+0.4W/m2/decade in 2000-2009 to +0.6W/m2/decade in 2010-2019), the majority of which is driven by changes in the aerosol ERF trend, due to aerosol emissions reductions. Here we study the extent to which observations of the climate system agree with these ERF assumptions. We use a large ERF ensemble from IPCC’s Sixth Assessment Report (AR6) to attribute the anthropogenic contributions to global mean surface temperature (GMST), top-of-atmosphere radiative flux, and aerosol optical depth observations. The GMST trend has increased from +0.18°C/decade in 2000-2009 to +0.35°C/decade in 2010-2019, coinciding with the anthropogenic warming trend rising from +0.19°C/decade in 2000-2009 to +0.24°C/decade in 2010-2019. This, and observed trends in top-of-atmosphere radiative fluxes and aerosol optical depths support the claim of an aerosol-induced temporary acceleration in the rate of warming. However, all three observation datasets additionally suggest smaller aerosol ERF trend changes are compatible with observations since 2000, since radiative flux and GMST trends are significantly influenced by internal variability over this period. A zero-trend-change aerosol ERF scenario results in a much smaller anthropogenic warming acceleration since 2000, but is poorly represented in AR6’s ERF ensemble. Short-term ERF trends are difficult to verify using observations, so caution is required in predictions or policy judgments that depend on them, such as estimates of current anthropogenic warming trend, and the time remaining to, or the outstanding carbon budget consistent with, 1.5°C warming. Further systematic research focused on quantifying trends and early identification of acceleration or deceleration is required.

Abstract:

Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide “opportunistic experiments” (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.