Current Earth Observation (EO) satellites provide excellent spatial, temporal and spectral coverage for passive measurements of atmospheric volcanic emissions. Of particular value for ash detection and quantification are the geostationary satellites that now carry multispectral imagers. These instruments have multiple spectral channels spanning the visible to infrared (IR) wavelengths and provide 1 × 1 km² to 4 × 4 km² resolution data every 5–15 min, continuously. For ash detection, two channels situated near 11 and 12 $\mathsf{\mu }$ m are needed; for ash quantification a third or fourth channel also in the infrared is useful for constraining the height of the ash cloud. This work describes passive EO infrared measurements and techniques to determine volcanic cloud properties and includes examples using current methods with an emphasis on the main difficulties and ways to overcome them. A challenging aspect of using satellite data is to design algorithms that make use of the spectral, temporal (especially for geostationary sensors) and spatial information. The hyperspectral sensor AIRS is used to identify specific molecules from their spectral signatures (e.g., for SO₂) and retrievals are demonstrated as global, regional and hemispheric maps of AIRS column SO₂. This kind of information is not available on all sensors, but by combining temporal, spatial and broadband multi-spectral information from polar and geo sensors (e.g., MODIS and SEVIRI) useful insights can be made. For example, repeat coverage of a particular area using geostationary data can reveal temporal behaviour of broadband channels indicative of eruptive activity. In many instances, identifying the nature of a pixel (clear, cloud, ash etc.) is the major challenge. Sophisticated cloud detection schemes have been developed that utilise statistical measures, physical models and temporal variation to classify pixels. The state of the art on cloud detection is good, but improvements are always needed. An IR-based multispectral cloud identification scheme is described and some examples shown. The scheme is physically based but has deficiencies that can be improved during the daytime by including information from the visible channels. Physical retrieval schemes applied to ash detected pixels suffer from a lack of knowledge of some basic microphysical and optical parameters needed to run the retrieval models. In particular, there is a lack of accurate spectral refractive index information for ash particles. The size distribution of fine ash (1–63 $\mathsf{\mu }$ m, diameter) is poorly constrained and more measurements are needed, particularly for ash that is airborne. Height measurements are also lacking and a satellite-based stereoscopic height retrieval is used to illustrate the value of this information for aviation. The importance of water in volcanic clouds is discussed here and the separation of ice-rich and ash-rich portions of volcanic clouds is analysed for the first time. More work is required in trying to identify ice-coated ash particles, and it is suggested that a class of ice-rich volcanic cloud be recognized and termed a ‘volcanic ice’ cloud. Such clouds are frequently observed in tropical eruptions of great vertical extent (e.g., 8 km or higher) and are often not identified correctly by traditional IR methods (e.g., reverse absorption). Finally, the global, hemispheric and regional sampling of EO satellites is demonstrated for a few eruptions where the ash and SO ${}_2$ dispersed over large distances (1000s km).

We report on the detection of giant pulses from the Crab Nebula pulsar at a frequency of 200 MHz using the field deployment system designed for the Mileura Widefield Array's Low Frequency Demonstrator (MWA-LFD). Our observations are among the first high-quality detections at such low frequencies. The measured pulse shapes are deconvolved for interstellar pulse broadening, yielding a pulse-broadening time of 670$\pm$100 $\mu$s, and the implied strength of scattering (scattering measure) is the lowest that is estimated towards the Crab nebula from observations made so far. The sensitivity of the system is largely dictated by the sky background, and our simple equipment is capable of detecting pulses that are brighter than $\sim$9 kJy in amplitude. The brightest giant pulse detected in our data has a peak amplitude of $\sim$50 kJy, and the implied brightness temperature is $10^{31.6}$ K. We discuss the giant pulse detection prospects with the full MWA-LFD system. With a sensitivity over two orders of magnitude larger than the prototype equipment, the full system will be capable of detecting such bright giant pulses out to a wide range of Galactic distances; from $\sim$8 to $\sim$30 kpc depending on the frequency. The MWA-LFD will thus be a highly promising instrument for the studies of giant pulses and other fast radio transients at low frequencies.Comment: 10 pages, 6 figures, Accepted for publication in the Astrophysical Journa

Changes in storm-triggered landslide activity for Southern California in a future warming climate are estimated using an advanced, fully three-dimensional, process-based landslide model, the Scalable and Extensible Geofluid Modeling System for landslides (SEGMENT-Landslide). SEGMENT-Landslide is driven by extreme rainfall projections from the Geophysical Fluid Dynamics Laboratory High Resolution Atmospheric Model (GFDL-HIRAM). Landslide changes are derived from GFDL-HIRAM forcing for two periods: 1) the twentieth century (CNTRL) and 2) the twenty-first century under the moderate Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios A1B enhanced greenhouse gas emissions scenario (EGHG). Here, differences are calculated in landslide frequency and magnitude between the CNTRL and EGHG projections; kernel density estimation (KDE) is used to determine differences in projected landslide locations. This study also reveals that extreme precipitation events in Southern California are strongly correlated with several climate drivers and that GFDL-HIRAM simulates well the southern (relative to Aleutian synoptic systems) storm tracks in El Niño years and the rare (~27-yr recurrence period) hurricane-landfalling events. GFDL-HIRAM therefore can provide satisfactory projections of the geographical distribution, seasonal cycle, and interannual variability of future extreme precipitation events (>50 mm) that have possible landslide consequences for Southern California. Although relatively infrequent, extreme precipitation events contribute most of the annual total precipitation in Southern California. Two findings of this study have major implications for Southern California. First is a possible increase in landslide frequency and areal distribution during the twenty-first century. Second, the KDE reveals three clusters in both the CNTRL and EGHG model mean scarp positions, with a future eastward (inland) shift of ~0.5° and a northward shift of ~1°. These findings suggest that previously stable areas might become susceptible to storm-triggered landslides in the twenty-first century.

Atmospheric turbulence primarily originates from abrupt density variations in a vertically stratified atmosphere. Based on the prognostic equation of turbulent kinetic energy (TKE), we here chose three indicators corresponding to the forcing terms of the TKE generation. By utilizing ERA5 reanalysis data, we investigate first the maximum achievable daily thickness of the planetary boundary layer (PBL). The gradient Richardson number (R_i) is used to represent turbulence arising from shear instability and the daily maximum convective available potential energy (CAPE) is examined to understand the turbulence linked with convective instability. Our analysis encompasses global turbulence trends. As a case study, we focus on the North Atlantic Corridor (NAC) to reveal notable insights. Specifically, the mean annual number of hours featuring shear instability (R_i < 0.25) surged by more than 300 h in consecutive 20-year periods: 1979–1998 and 1999–2018. Moreover, a substantial subset within the NAC region exhibited a notable rise of over 10% in the number of hours characterized as severe shear instability. Contrarily, turbulence associated with convective instability (CAPE > 2 kJ/kg), which can necessitate rerouting and pose significant aviation safety challenges, displays a decline. Remote sensing of clouds confirms these assertions. This decline contains a component of inherent natural variability. Our findings suggest that, as air viscosity increases and hence a thickened PBL due to a warming climate, the global inflight turbulence is poised to intensify.