On 15 January 2022, the Hunga Tonga‐Hunga Ha'apai eruption injected SO₂ and H₂O into the middle stratosphere. The eruption produced a persistent mid‐stratospheric sulfate aerosol and H₂O layer mostly confined to Southern Hemisphere (SH) tropics (Eq. to 30°S). These layers are still present in the tropics 5½ months after the eruption. The SH tropical confinement is simulated using a trajectory model. Measurements following the eruption show that the H₂O layer is slowly rising while the aerosol layer is descending. The H₂O layer's upward movement is consistent with the residual vertical velocity. Gravitationally settling explains the descent of the aerosol layer. A −4 K temperature anomaly coincident with the H₂O enhancement is observed and is caused by thermal adjustment to the additional H₂O IR cooling. A simple model of volcanic water injection at the time of the eruption simulates the observed vertical distribution H₂O.

We calculate the climate forcing for the 2 ys after the 15 January 2022, Hunga Tonga‐Hunga Ha'apai (Hunga) eruption. We use satellite observations of stratospheric aerosols, trace gases and temperatures to compute the tropopause radiative flux changes relative to climatology. Overall, the net downward radiative flux decreased compared to climatology. The Hunga stratospheric water vapor anomaly initially increases the downward infrared radiative flux, but this forcing diminishes as the anomaly disperses. The Hunga aerosols cause a solar flux reduction that dominates the net flux change over most of the 2 yrs period. Hunga induced temperature changes produce a decrease in downward long‐wave flux. Hunga induced ozone reduction increases the short‐wave downward flux creating small sub‐tropical increase in total flux from mid‐2022 to 2023. By the end of 2023, most of the Hunga induced radiative forcing changes have disappeared. There is some disagreement in the satellite measured stratospheric aerosol optical depth (SAOD) observations which we view as a measure of the uncertainty; however, the SAOD uncertainty does not alter our conclusion that, overall, aerosols dominate the radiative flux changes.

On 15 January 2022, the Hunga Tonga‐Hunga Ha'apai (HT) eruption injected SO₂ and water into the middle stratosphere. The SO₂ is rapidly converted to sulfate aerosols. The aerosol and water vapor anomalies have persisted in the Southern Hemisphere throughout 2022. The water vapor anomaly increases the net downward IR radiative flux whereas the aerosol layer reduces the direct solar forcing. The direct solar flux reduction is larger than the increased IR flux. Thus, the net tropospheric forcing will be negative. The changes in radiative forcing peak in July and August and diminish thereafter. Scaling to the observed cooling after the 1991 Pinatubo eruption, HT would cool the 2022 Southern Hemisphere's average surface temperatures by less than 0.037°C.

On 15 January 2022, the Hunga Tonga‐Hunga Ha'apai (HT) eruption injected SO₂ and water into the middle stratosphere. Shortly after the eruption, the water vapor anomaly moved northward toward and across the equator. This northward movement appears to be due to equatorial Rossby waves forced by the excessive infrared water vapor cooling. Following the early eruption stage, persistent mid‐stratospheric water vapor and aerosol layers were mostly confined to Southern Hemisphere tropics (Eq. to 30°S). However, during the spring of 2022, the westerly phase of the tropical quasi‐biennial oscillation (QBO) descended through the tropics. The HT water vapor and aerosol anomalies were observed to again move across the equator coincident with the shift in the Brewer‐Dobson circulation and the descent of the QBO shear zone.

We describe our Solar Aerosol and Gas Experiment (SAGE) III/ISS cloud detection algorithm and observations. We identify three types of clouds: visible cirrus (extinction coefficient > 3 x 10⁻² km⁻¹), subvisible cirrus (extinction coefficient between 3 x 10⁻² km⁻¹ and 10⁻³ km⁻¹), and very low extinction cloud‐aerosol mixtures (extinction coefficient between 10⁻³ km⁻¹and 10⁻⁴ km⁻¹). Visible cirrus cannot be quantitatively measured by SAGE because of its high extinction, but we infer the presence of cirrus through the termination of the SAGE vertical scan. We then assume that cirrus layers extend 0.5 km below the scan termination height. SAGE cirrus cloud fraction estimated in this way is in qualitative agreement with Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements. Analyzing 2018–2020 SAGE III/ISS data, we find that visible cirrus and subvisible cirrus have nearly equal abundance in the tropical upper troposphere and the average cloud fraction is about 25%. At 16 km, the highest concentration of visible cirrus and subvisible cirrus is over the Tropical West Pacific, central Africa, and central South America during boreal winter. Latitudinal gaps in zonal mean cloud fraction are aligned with descending branch of the residual mean circulation. Using tropopause relative coordinates, we show that maximum cloud‐top heights are consistently restricted to a narrow region near the tropopause. The aerosol extinction fields also show the latitudinal gaps coincident with the descending residual circulation. We identify four anomalous aerosol extinction periods that can be tentatively assigned to significant volcanic or fire events.

The Multi‐angle Imaging SpectroRadiometer (MISR) provides measurements over a wider scattering‐angle range for a given location than a cross‐track scanning sensor such as the MODerate resolution Imaging Spectroradiometer (MODIS). Based on a full year (2013) of fused MISR‐MODIS datasets, we develop a variable surface roughness model for ice particles with the goal of identifying the optimal degree of roughness in the ice model for a given pixel containing single‐layer ice clouds. For the MISR‐MODIS observations over oceans, severe roughness values are often selected for a pixel when optical thickness (τ) and particle effective radius (R_eff) are large in conjunction with larger cloud heterogeneity index (H_σ) or a warmer cloud top temperature. Furthermore, τ, R_eff, and ice water path are retrieved with the optimal model and compared to operational MODIS Collection 6 (MC6) products that assume a constant roughness. In general, the retrievals based on the present optimal model lead to greater consistency with MISR measurements, and result in larger median τ by 10.1% and smaller median R_eff by 6.5% but almost identical ice water path in comparison with the MC6 counterparts. The higher average τ value is caused by a slightly larger number of large τ cases, but the smaller average R_eff value is due to the shifting of the retrieved R_eff value toward smaller values by approximately 2–4 μm in comparison to the MC6 distribution over all seasons. Both τ retrievals have similar regional and monthly variations, but a larger annual cycle of R_eff is associated with the optimal model.