ALBERT

Description: The concept of cloud radiative forcing (CRF) is commonly applied to quantify the impact of clouds on the surface radiative energy budget (REB). In the Arctic, specific radiative interactions between microphysical and macrophysical properties of clouds and the surface strongly modify the warming or cooling effect of clouds, complicating the estimate of CRF obtained from observations or models. Clouds tend to increase the broadband surface albedo over snow or sea ice surfaces compared to cloud-free conditions. However, this effect is not adequately considered in the derivation of CRF in the Arctic so far. Therefore, we have quantified the effects caused by surface-albedo–cloud interactions over highly reflective snow or sea ice surfaces on the CRF using radiative transfer simulations and below-cloud airborne observations above the heterogeneous springtime marginal sea ice zone (MIZ) during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign. The impact of a modified surface albedo in the presence of clouds, as compared to cloud-free conditions, and its dependence on cloud optical thickness is found to be relevant for the estimation of the shortwave CRF. A method is proposed to consider this surface albedo effect on CRF estimates by continuously retrieving the cloud-free surface albedo from observations under cloudy conditions, using an available snow and ice albedo parameterization. Using ACLOUD data reveals that the estimated average shortwave cooling by clouds almost doubles over snow- and ice-covered surfaces (−62 W m−2 instead of −32 W m−2), if surface-albedo–cloud interactions are considered. As a result, the observed total (shortwave plus longwave) CRF shifted from a warming effect to an almost neutral one. Concerning the seasonal cycle of the surface albedo, it is demonstrated that this effect enhances shortwave cooling in periods when snow dominates the surface and potentially weakens the cooling by optically thin clouds during the summertime melting season. These findings suggest that the surface-albedo–cloud interaction should be considered in global climate models and in long-term studies to obtain a realistic estimate of the shortwave CRF to quantify the role of clouds in Arctic amplification.

Description: As knowledge about the cirrus clouds in the lower stratosphere is limited, reliable long-term measurements are needed to assess their characteristics, radiative impact and important role in upper troposphere and lower stratosphere (UTLS) chemistry. We used 6 years (2006–2012) of Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) measurements to investigate the global and seasonal distribution of stratospheric cirrus clouds and compared the MIPAS results with results derived from the latest version (V4.x) of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data. For the identification of stratospheric cirrus clouds, precise information on both the cloud top height (CTH) and the tropopause height is crucial. Here, we used lapse rate tropopause heights estimated from the ERA-Interim global reanalysis. Considering the uncertainties of the tropopause heights and the vertical sampling grid, we define CTHs more than 0.5 km above the tropopause as stratospheric for CALIPSO data. For MIPAS data, we took into account the coarser vertical sampling grid and the broad field of view so that we considered cirrus CTHs detected more than 0.75 km above the tropopause as stratospheric. Further sensitivity tests were conducted to rule out sampling artefacts in MIPAS data. The global distribution of stratospheric cirrus clouds was derived from night-time measurements because of the higher detection sensitivity of CALIPSO. In both data sets, MIPAS and CALIPSO, the stratospheric cirrus cloud occurrence frequencies are significantly higher in the tropics than in the extra-tropics. Tropical hotspots of stratospheric cirrus clouds associated with deep convection are located over equatorial Africa, South and Southeast Asia, the western Pacific, and South America. Stratospheric cirrus clouds were more often detected in December–February (15 %) than June–August (8 %) in the tropics (±20∘). At northern and southern middle latitudes (40–60∘), MIPAS observed about twice as many stratospheric cirrus clouds (occurrence frequencies of 4 %–5 % for MIPAS rather than about 2 % for CALIPSO). We attribute more frequent observations of stratospheric cirrus clouds with MIPAS to the higher detection sensitivity of the instrument to optically thin clouds. In contrast to the difference between daytime and night-time occurrence frequencies of stratospheric cirrus clouds by a factor of about 2 in zonal means in the tropics (4 % and 10 %, respectively) and at middle latitudes for CALIPSO data, there is little diurnal cycle in MIPAS data, in which the difference of occurrence frequencies in the tropics is about 1 percentage point in zonal mean and about 0.5 percentage point at middle latitudes. The difference between CALIPSO day and night measurements can also be attributed to their differences in detection sensitivity. Future work should focus on better understanding the origin of the stratospheric cirrus clouds and their impact on radiative forcing and climate.

Description: Calculating a multi-model mean, a commonly used method for ensemble averaging, assumes model independence and equal model skill. Sharing of model components amongst families of models and research centres, conflated by growing ensemble size, means model independence cannot be assumed and is hard to quantify. We present a methodology to produce a weighted-model ensemble projection, accounting for model performance and model independence. Model weights are calculated by comparing model hindcasts to a selection of metrics chosen for their physical relevance to the process or phenomena of interest. This weighting methodology is applied to the Chemistry–Climate Model Initiative (CCMI) ensemble to investigate Antarctic ozone depletion and subsequent recovery. The weighted mean projects an ozone recovery to 1980 levels, by 2056 with a 95 % confidence interval (2052–2060), 4 years earlier than the most recent study. Perfect-model testing and out-of-sample testing validate the results and show a greater projective skill than a standard multi-model mean. Interestingly, the construction of a weighted mean also provides insight into model performance and dependence between the models. This weighting methodology is robust to both model and metric choices and therefore has potential applications throughout the climate and chemistry–climate modelling communities.

Description: Accurate reference spectroscopic information for the water molecule from the microwave to the near-ultraviolet is of paramount importance in atmospheric research. A semi-empirical potential energy surface for the ground electronic state of H216O has been created by refining almost 4000 experimentally determined energy levels. These states extend into regions with large values of rotational and vibrational excitation. For all states considered in our refinement procedure, which extend to 37 000 cm−1 and J=20 (total angular momentum), the average root-mean-square deviation is approximately 0.05 cm−1. This potential energy surface offers significant improvements when compared to recent models by accurately predicting states possessing high values of J. This feature will offer significant improvements in calculated line positions for high-temperature spectra where transitions between high J states become more prominent. Combining this potential with the latest dipole moment surface for water vapour, a line list has been calculated which extends reliably to 37 000 cm−1. Obtaining reliable results in the ultraviolet is of special importance as it is a challenging spectral region for the water molecule both experimentally and theoretically. Comparisons are made against several experimental sources of cross sections in the near-ultraviolet and discrepancies are observed. In the near-ultraviolet our calculations are in agreement with recent atmospheric retrievals and the upper limit obtained using broadband spectroscopy by Wilson et al. (2016, p. 194), but they do not support recent suggestions of very strong absorption in this region.

Description: North African dust reaches the southeastern United States every summer. Size-resolved dust mass measurements taken in Miami, Florida, indicate that more than one-half of the surface dust mass concentrations reside in particles with geometric diameters less than 2.1 µm, while vertical profiles of micropulse lidar depolarization ratios show dust reaching above 4 km during pronounced events. These observations are compared to the representation of dust in the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) aerosol reanalysis and closely related Goddard Earth Observing System model version 5 (GEOS-5) Forward Processing (FP) aerosol product, both of which assimilate satellite-derived aerosol optical depths using a similar protocol and inputs. These capture the day-to-day variability in aerosol optical depth well, in a comparison to an independent sun-photometer-derived aerosol optical depth dataset. Most of the modeled dust mass resides in diameters between 2 and 6 µm, in contrast to the measurements. Model-specified mass extinction efficiencies equate light extinction with approximately 3 times as much aerosol mass, in this size range, compared to the measured dust sizes. GEOS-5 FP surface-layer sea salt mass concentrations greatly exceed observed values, despite realistic winds and relative humidities. In combination, these observations help explain why, despite realistic total aerosol optical depths, (1) free-tropospheric model volume extinction coefficients are lower than those retrieved from the micro-pulse lidar, suggesting too-low model dust loadings in the free troposphere, and (2) model dust mass concentrations near the surface can be higher than those measured. The modeled vertical distribution of dust, when captured, is reasonable. Large, aspherical particles exceeding the modeled dust sizes are also occasionally present, but dust particles with diameters exceeding 10 µm contribute little to the measured total dust mass concentrations after such long-range transport. Remaining uncertainties warrant a further integrated assessment to confirm this study's interpretations.

Description: Summary On 24th August 2016 at 01:36 UTC a ML6.0 earthquake struck several villages in central Italy, among which Accumoli, Amatrice and Arquata del Tronto. The earthquake was recorded by about 350 seismic stations, causing 299 fatalities and damage with macroseismic intensities up to 11. The maximum acceleration was observed at Amatrice station (AMT) reaching 916 cm/s2 on E-W component, with epicentral distance of 15 km and Joyner and Boore distance to the fault surface (RJB) of less than a kilometre. Motivated by the high levels of observed ground motion and damage, we generate broadband seismograms for engineering purposes by adopting a hybrid method. To infer the low frequency seismograms, we considered the kinematic slip model by Tinti et al. (2016). The high frequency seismograms were produced using a stochastic finite-fault model approach based on dynamic corner-frequency. Broadband synthetic time series were therefore obtained by merging the low and high frequency seismograms. Simulated hybrid ground motions were compared both with the observed ground motions and the ground-motion prediction equations (GMPEs), to explore their performance and to retrieve the region-specific parameters endorsed for the simulations. In the near-fault area we observed that hybrid simulations have a higher capability to detect near source effects and to reproduce the source complexity than the use of GMPEs. Indeed, the general good consistency found between synthetic and observed ground motion (both in the time and frequency domain), suggests that the use of regional-specific source scaling and attenuation parameters together with the source complexity in hybrid simulations improves ground motion estimations. To include the site effect in stochastic simulations at selected stations, we tested the use of amplification curves derived from HVRSs (horizontal-to-vertical response spectra) and from HVSRs (horizontal-to-vertical spectral ratios) rather than the use of generic curves according to NTC-18 Italian seismic design code. We generally found a further reduction of residuals between observed and simulated both in terms of time histories and spectra.

Description: Summary We explore here the benefits of using constraints from seismic tomography in gravity data inversion and how inverted density distributions can be improved by doing so. The methodology is applied to a real field case in which we reconstruct the density structure of the Pyrenees along a southwest-northeast transect going from the Ebro basin in Spain to the Arzacq basin in France. We recover the distribution of densities by inverting gravity anomalies under constraints coming from seismic tomography. We initiate the inversion from a prior density model obtained by scaling a pre-existing compressional seismic velocity Vp model using a Nafe-Drake relationship : the Vp model resulting from a full-waveform inversion of teleseismic data. Gravity data inversions enforce structural similarities between Vp and density by minimizing the norm of the cross-gradient between the density and Vp models. We also compare models obtained from 2.5D and 3D inversions. Our results demonstrate that structural constraints allow us to better recover the density contrasts close to the surface and at depth, without degrading the gravity data misfit. The final density model provides valuable information on the geological structures and on the thermal state and composition of the western region of the Pyrenean lithosphere.

Description: Summary The relatively short duration of the early stages of subduction results in a poor geological record, limiting our understanding of this critical stage. Here, we utilize a 2D numerical model of incipient subduction, that is the stage after a plate margin has formed with a slab tip that extends to a shallow depth and address the conditions under which subduction continues or fails. We assess energy budgets during the evolution from incipient subduction to either a failed or successful state, showing how the growth of potential energy, and slab pull, is resisted by the viscous dissipation within the lithosphere and the mantle. The role of rheology is also investigated, as deformation mechanisms operating in the crust and mantle facilitate subduction. In all models, the onset of subduction is characterized by high lithospheric viscous dissipation and low convergence velocities, whilst successful subduction sees the mantle become the main area of viscous dissipation. In contrast, failed subduction is defined by the lithospheric viscous dissipation exceeding the lithospheric potential energy release rate and velocities tend towards zero. We show that development of a subduction zone depends on the convergence rate, required to overcome thermal diffusion and to localise deformation along the margin. The results propose a minimum convergence rate of ∼ 0.5 cm yr−1 is required to reach a successful state, with 100 km of convergence over 20 Myr, emphasizing the critical role of the incipient stage.

Description: Summary Although many studies have revealed that the atmospheric effects of electromagnetic wave propagation (including ionospheric and tropospheric water vapor) have serious impacts on Interferometric Synthetic Aperture Radar (InSAR) measurement results, atmospheric corrections have not been thoroughly and comprehensively investigated in many well-known cases of InSAR focal mechanism solutions, which means there is no consensus on whether atmospheric effects will affect the InSAR focal mechanism solution. Moreover, there is a lack of quantitative assessment on how much the atmospheric effect affects the InSAR focal mechanism solution. In this paper, we emphasized that it was particularly important to assess the impact of InSAR ionospheric and tropospheric corrections on the underground nuclear explosion modeling quantitatively. Therefore, we investigated the 4th North Korea (NKT-4) underground nuclear test using ALOS-2 liters-band SAR images. Because the process of the underground nuclear explosion was similar to the volcanic magma source activity, we modeled the ground displacement using the Mogi model. Both the ionospheric and tropospheric phase delays in the interferograms were investigated. Furthermore, we studied how the ionosphere and troposphere phase delays could bias the estimation of Mogi source parameters. The following conclusions were drawn from our case study: The ionospheric delay correction effectively mitigated the long-scale phase ramp in the full-frame interferogram, the standard deviation decreased from 1.83 cm to 0.85 cm compared to the uncorrected interferogram. The uncorrected estimations of yield and depth were 8.44 kt and 370.33 m, respectively. Compared to the uncorrected estimations, the ionospheric correction increased the estimation of yield and depth to 9.43 kt and 385.48 m while the tropospheric correction slightly raised them to 8.78 kt and 377.24 m. There were no obvious differences in the location estimations among the four interferograms. When both corrections were applied, the overall standard deviation was 1.16 cm, which was even larger than the ionospheric corrected interferogram. We reported the source characteristics of NKT-4 based on the modeling results derived from the ionospheric corrected interferogram. The preferred estimation of NKT-4 was a Mogi source located at 129°04′22.35‘E, 41°17′54.57″N buried at 385.48 m depth. The cavity radius caused by the underground explosion was 22.02 m. We reported the yield estimation to be 9.43 kt. This study showed that for large-scale natural deformation sources such as volcanoes and earthquakes, atmospheric corrections would be more significant, but even if the atmospheric signal did not have much complexity, the corrections should not be ignored.

Description: SUMMARY Self-consistent modelling of magmatic systems is challenging as the melt continuously changes its chemical composition upon crystallization, which may affect the mechanical behaviour of the system. Melt extraction and subsequent crystallization create new rocks while depleting the source region. As the chemistry of the source rocks changes locally due to melt extraction, new calculations of the stable phase assemblages are required to track the rock evolution and the accompanied change in density. As a consequence, a large number of isochemical sections of stable phase assemblages are required to study the evolution of magmatic systems in detail. As the state-of-the-art melting diagrams may depend on nine oxides as well as pressure and temperature, this is a 10-D computational problem. Since computing a single isochemical section (as a function of pressure and temperature) may take several hours, computing new sections of stable phase assemblages during an ongoing geodynamic simulation is currently computationally intractable. One strategy to avoid this problem is to pre-compute these stable phase assemblages and to create a comprehensive database as a hyperdimensional phase diagram, which contains all bulk compositions that may emerge during petro-thermomechanical simulations. Establishing such a database would require repeating geodynamic simulations many times while collecting all requested compositions that may occur during a typical simulation and continuously updating the database until no additional compositions are required. Here, we describe an alternative method that is better suited for implementation on large-scale parallel computers. Our method uses the entries of an existing preliminary database to estimate future required chemical compositions. Bulk compositions are determined within boundaries that are defined manually or through principal component analysis in a parameter space consisting of clustered database entries. We have implemented both methods within a massively parallel computational framework while utilizing the Gibbs free energy minimization program Perple_X. Results show that our autonomous approach increases the resolution of the thermodynamic database in compositional regions that are most likely required for geodynamic models of magmatic systems.