The 15 January 2022 climactic eruption of Hunga volcano, Tonga, produced an explosion in the atmosphere of a size that has not been documented in the modern geophysical record. The event generated a broad range of atmospheric waves observed globally by various ground-based and spaceborne instrumentation networks. Most prominent is the surface-guided Lamb wave ( ≲ 0.01 Hz), which we observed propagating for four (+three antipodal) passages around the Earth over six days. Based on Lamb wave amplitudes, the climactic Hunga explosion was comparable in size to that of the 1883 Krakatau eruption. The Hunga eruption produced remarkable globally-detected infrasound (0.01–20 Hz), long-range (~10,000 km) audible sound, and ionospheric perturbations. Seismometers worldwide recorded pure seismic and air-to-ground coupled waves. Air-to-sea coupling likely contributed to fast-arriving tsunamis. We highlight exceptional observations of the atmospheric waves.

Abstract. This paper gives an update of the RTTOV (Radiative Transfer for TOVS) fast radiative transfer model, which is widely used in the satellite retrieval and data assimilation communities. RTTOV is a fast radiative transfer model for simulating top-of-atmosphere radiances from passive visible, infrared and microwave downward-viewing satellite radiometers. In addition to the forward model, it also optionally computes the tangent linear, adjoint and Jacobian matrix providing changes in radiances for profile variable perturbations assuming a linear relationship about a given atmospheric state. This makes it a useful tool for developing physical retrievals from satellite radiances, for direct radiance assimilation in NWP models, for simulating future instruments, and for training or teaching with a graphical user interface. An overview of the RTTOV model is given, highlighting the updates and increased capability of the latest versions, and it gives some examples of its current performance when compared with more accurate line-by-line radiative transfer models and a few selected observations. The improvement over the original version of the model released in 1999 is demonstrated.

[1] Monitoring of atmospheric methane (CH 4 ) concentrations from space-based instruments such as the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and the Greenhouse Gases Observing Satellite (GOSAT) relies on observations of sunlight backscattered to space by the Earth's surface and atmosphere. Retrieval biases occur due to unaccounted scattering effects by aerosols and thin cirrus that modify the lightpath. Here, we evaluate the accuracy of two retrieval methods that aim at minimizing such scattering induced errors. The lightpath "proxy" method, applicable to SCIAMACHY and GOSAT, retrieves CH 4 and carbon dioxide (CO 2 ) simultaneously and uses CO 2 as a proxy for lightpath modification. The "physics-based" method, which we propose for GOSAT, aims at simultaneously retrieving CH 4 concentrations and scattering properties of the atmosphere. We evaluate performance of the methods against a trial ensemble of simulated aerosol and cirrus loaded scenes. More than 80% of the trials yield residual scattering induced CH 4 errors below 0.6% and 0.8% for the proxy and the physics-based approach, respectively. Very few cases result in errors greater than 2% for both methods. Advantages of the proxy approach are efficient and robust performance yielding more useful retrievals than the physics-based method which reveals some nonconvergent cases. The major disadvantage of the proxy method is the uncertainty of the proxy CO 2 concentration contributing to the overall error budget. Residual errors generally correlate with particle and surface properties and thus might impact inverse modeling of CH 4 sources and sinks.Citation: Butz, A., O. P. Hasekamp, C. Frankenberg, J. Vidot, and I. Aben (2010), CH 4 retrievals from space-based solar backscatter measurements: Performance evaluation against simulated aerosol and cirrus loaded scenes,