Weak Events Research Articles

Impacts of different types of El Niño and La Niña on northern tropical Atlantic sea surface temperature

The present study investigates the dependence of the northern tropical Atlantic (NTA) sea surface temperature (SST) response to El Nino and La Nina events on the decay time and amplitude of tropical Pacific SST anomalies. It is found that the NTA SST response to La Nina events displays a notable difference between late and early decaying events, similar to that in response to El Nino events, but with a weaker signal. Latent heat flux is a dominant term in the NTA SST change in preceding winter-early spring in both El Nino and La Nina events and in the difference of the NTA SST anomaly between late and early decaying El Nino and La Nina events. The zonal and meridional advections have an opposite effect on the NTA SST warming in late decaying El Nino events. Although the warming in the NTA region is similar in late decaying moderate and strong El Nino events, the distribution of the SST anomalies in the mid-latitude North Atlantic Ocean shows a notable difference between the two types of late decaying El Nino events. The SST anomalies also display difference in the early decaying weak and moderate El Nino events. Surface heat flux differences are largely attributed to wind differences.

A Process-Based Validation of GPM IMERG and Its Sources Using a Mesoscale Rain Gauge Network in the West African Forest Zone

AbstractUsing a two-year dataset (2016–17) from 17 one-minute rain gauges located in the moist forest region of Ghana, the performance of Integrated Multisatellite Retrievals for GPM, version 6b (IMERG), is evaluated based on a subdaily time scale, down to the level of the underlying passive microwave (PMW) and infrared (IR) sources. Additionally, the spaceborne cloud product Cloud Property Dataset Using SEVIRI, edition 2 (CLAAS-2), available every 15 min, is used to link IMERG rainfall to cloud-top properties. Several important issues are identified: 1) IMERG’s proneness to low-intensity false alarms, accounting for more than a fifth of total rainfall; 2) IMERG’s overestimation of the rainfall amount from frequently occurring weak convective events, while that of relatively rare but strong mesoscale convective systems is underestimated, resulting in an error compensation; and 3) a decrease of skill during the little dry season in July and August, known to feature enhanced low-level cloudiness and warm rain. These findings are related to 1) a general oversensitivity for clouds with low ice and liquid water path and a particular oversensitivity for low cloud optical thickness, a problem which is slightly reduced for direct PMW overpasses; 2) a pronounced negative bias for high rain intensities, strongest when IR data are included; and 3) a large fraction of missed events linked with rainfall out of warm clouds, which are inherently misinterpreted by IMERG and its sources. This paper emphasizes the potential of validating spaceborne rainfall products with high-resolution rain gauges on a subdaily time scale, particularly for the understudied West African region.

Современные сейсмологические исследования в Латвии с 2008 по 2019 г. и перспективы их развития

In Latvia, seismological monitoring has been carried out at Slitere station since 2006. Slitere station is part of the GEOFON international network, with its center at GFZ Potsdam. The use of other stations of the GEOFON network and some stations of national networks of Finland and Estonia allows monitoring the entire East Baltic Region (VBR), including Estonia, Latvia, Lithuania, the Kaliningrad Region of Russia, and the adjacent part of the Baltic Sea (Lat=53.9°N - 59.7°N; Lon=19.4°E - 29.6°E). The impetus for the development of seismological monitoring was the Kaliningrad earthquakes of 2004 with Mw 5.0 and 5.2. The main object of research, in addition to tectonic earthquakes, is man-made seismicity, which prevails in Latvia and in EBR. Because of seismic monitoring for the period from 2008 to 2019, 8 tectonic earthquakes were localized, as well as more than 5640 man-made seismic events. The total number of seismic events localized by the BAVSEN network is 13328, including 1096 teleseismic events. The relevance of seismological monitoring is increasing due to unfavorable geodynamic conditions in the area where some large energy, transport facilities, and agglomerations are located, which requires a study of the seismic regime of the territories around these objects. The main problems of EBR seismic monitoring are associated with the identification of relatively weak seismic events, with a rare network of seismic stations, adverse seismic and geological conditions of the sedimentary cover, and low activity of EBR tectonic earthquakes. The lack of promising methods for recognizing the genesis of seismic events puts this problem in the first place. The prospects for seismological research in Latvia are related to the study of the seismic and geological properties of grounds, seismic micro zoning, monitoring of hydraulic structures, as well as the possibility of creating a National Data Center, within which seismological monitoring can become one of the main methods for radiation safety of EBR.

Бачатское техногенное землетрясение 18 июня 2013 г. с ML=6.1, I0=7 (Кузбасс)

The Bachatsky earthquake of 18 June 2013 and a seismic activation of the same name coal strip mine, started several years before the earthquake and still persists today, have been studied using temporal local seismic arrays in the area. It was found experimentally that the seismic process area is closely connected to open workings, and the earthquakes are extend-ed from the working bed to a depth of 4-5 km. Adjacent to the mine depression sedimentary rocks were activated. The technogenic seismic regime is continuous and not stationary: intervals of background seismicity with relatively weak and seldom events are disturbed by bursts of activity with a rise in the magnitude of stronger earthquakes and frequency of occurrence of weak events. The seismic activation may last for 1–3 months. During the last five years, four seismic activations have been recorded, three of which were generated by large earthquakes of 09.02.2012, ML4.3; 04.03.2013, ML3.9; 18.06.2013, ML6.1. The last one was completed by a series of perceptible earthquakes with local magnitude of 3.0–3.5. The focal mechanism of the Bachatsky earthquake is a thrust fault with one of the motion planes corresponding to the anthropogenic impact. The earthquake flow forms a single process in the space with the b-value of the Gutenberg-Richter relationship different from the natural seismicity. The studied induced seismicity does not correspond to the structural regularities of natural seismicity in the Altai-Sayan mountain area. The findings prove that the Bachatsky earthquake and associated activation can be considered as man-made events.

A model study of terraced riverbeds as novel ecosystems

Riverbed terracing has been introduced in ancient times to retain water and soil, to reduce hydrological connectivity and erosion and to increase primary and secondary productivity of agro-ecological systems. These presently abandoned human-made landscapes have become novel ecosystems and a potential source of ecosystem services to humans in drylands. We use a mathematical-modeling approach to study factors that regulate terraced riverbeds and affect community and ecosystem attributes such as productivity, functional diversity and resilience to droughts. We introduce a model that captures the relationships between rainfall pattern, runoff coupling between adjacent terraces, and vegetation growth, taking into account competition for water and light. We found that a large number of weak rainfall events results in lower total biomass and functional diversity across the terraced riverbed compared with a few strong rainfall events. We further analyzed the filtering of species traits from pools of functional groups that make different tradeoffs between investment in above-ground biomass to capture canopy resources and investment in below-ground biomass to capture soil resources. Pools characterized by concave tradeoffs give rise to higher functional diversity, lower biomass production and lower resilience to droughts, as compared with convex pools. New empirical studies are needed to test these model predictions.

Accurate porosity prediction for tight sandstone reservoir: A case study from North China

Tight sandstone reservoirs have complex petrophysical properties, which introduce difficulties to rock-physics modeling. Besides, weak reflection events appear with a high probability in the seismic profile for tight sandstones. By combining the soft-porosity model and Gassmann’s relation, weak reflection events are analyzed in detail, which can be contaminated by remaining internal multiples and the amplitudes may be lowered by the transmission loss. These pose challenges for the porosity prediction. To obtain the porosity estimate accurately of tight sandstone reservoirs, porosity prediction is performed in two steps. First, within the framework of Bayesian inversion, the elastic parameters are obtained with high accuracy by using the reflectivity method, which can effectively describe transmission loss and internal multiples. Second, the Bayes discriminant method is applied to predict porosity from the estimated elastic parameters. It avoids using deterministic rock-physics modeling because the difficulties in rock-physics modeling of tight sandstones make it hard to predict their petrophysical properties. To ensure the prediction accuracy, detailed lithology identification and sensitivity parameters analysis are performed. Different examples of well-logging data and seismic data demonstrate that our approach can well predict the porosity.

Spatio-Temporal Variability of Rainfall Indices and their Teleconnections with El Niño-Southern Oscillation for Tapi Basin, India

The long-term spatio-temporal variability in twelve rainfall indices across Tapi basin are investigated for period 1944–2013. The temporal trends in aforesaid indices, representing magnitude, intensity, frequency and duration of rainfall, are analysed using non-parametric tests. The total annual rainfall exhibit uniformly increasing trends over Lower Tapi basin (LTB), while heterogeneous trends are observed across Upper (UTB) and Middle (MTB) Tapi basins. The rainy days portrays decreasing trends at 75% stations in the basin, while rainfall intensity displays increasing trends across LTB and UTB. On other hand, LTB and Purna sub-catchment (in UTB) show coherent increasing trends in extreme rainfall, while decreasing trends are observed over Burhanpur sub-catchment (in UTB) and MTB. A considerable increase in duration of dry spells is reported at 92.5% stations in the basin, indicating a marked shift towards drier climatic regime. Further, Principal Component Analysis (PCA) is carried out to address the space-time variability of rainfall indices. The results of PCA were adopted in cluster analysis to identify the stations exhibiting similar characteristic variations in rainfall trends. The hydroclimatic teleconnections between rainfall indices and large-scale oceanic-atmospheric circulations of the tropical Pacific Ocean (viz., El Nino-Southern Oscillation) revealed the prevalence of wet conditions in the basin during moderate to strong La-Nina, while dry conditions were encountered during moderate to strong El-Nino and weak La-Nina events. The spatial estimates of rainfall indices are derived corresponding to 2-, 10- and 50-year return periods which would be helpful in hydrologic design and risk assessment of rainfall-induced disasters in near future.

Recent Advances and Challenges of Waveform‐Based Seismic Location Methods at Multiple Scales

AbstractSource locations provide fundamental information on earthquakes and lay the foundation for seismic monitoring at all scales. Seismic source location as a classical inverse problem has experienced significant methodological progress during the past century. Unlike the conventional traveltime‐based location methods that mainly utilize kinematic information, a new category of waveform‐based methods, including partial waveform stacking, time reverse imaging, wavefront tomography, and full waveform inversion, adapted from migration or stacking techniques in exploration seismology has emerged. Waveform‐based methods have shown promising results in characterizing weak seismic events at multiple scales, especially for abundant microearthquakes induced by hydraulic fracturing in unconventional and geothermal reservoirs or foreshock and aftershock activity potentially preceding tectonic earthquakes. This review presents a comprehensive summary of the current status of waveform‐based location methods, through elaboration of the methodological principles, categorization, and connections, as well as illustration of the applications to natural and induced/triggered seismicity, ranging from laboratory acoustic emission to field hydraulic fracturing‐induced seismicity, regional tectonic, and volcanic earthquakes. Taking into account recent developments in instrumentation and the increasing availability of more powerful computational resources, we highlight recent accomplishments and prevailing challenges of different waveform‐based location methods and what they promise to offer in the near future.

The Role of the Stratosphere in Subseasonal to Seasonal Prediction: 2. Predictability Arising From Stratosphere‐Troposphere Coupling

AbstractThe stratosphere can have a significant impact on winter surface weather on subseasonal to seasonal (S2S) timescales. This study evaluates the ability of current operational S2S prediction systems to capture two important links between the stratosphere and troposphere: (1) changes in probabilistic prediction skill in the extratropical stratosphere by precursors in the tropics and the extratropical troposphere and (2) changes in surface predictability in the extratropics after stratospheric weak and strong vortex events. Probabilistic skill exists for stratospheric events when including extratropical tropospheric precursors over the North Pacific and Eurasia, though only a limited set of models captures the Eurasian precursors. Tropical teleconnections such as the Madden‐Julian Oscillation, the Quasi‐Biennial Oscillation, and El Niño–Southern Oscillation increase the probabilistic skill of the polar vortex strength, though these are only captured by a limited set of models. At the surface, predictability is increased over the United States, Russia, and the Middle East for weak vortex events, but not for Europe, and the change in predictability is smaller for strong vortex events for all prediction systems. Prediction systems with poorly resolved stratospheric processes represent this skill to a lesser degree. Altogether, the analyses indicate that correctly simulating stratospheric variability and stratosphere‐troposphere dynamical coupling are critical elements for skillful S2S wintertime predictions.

Non-linear modulation of site response: Sensitivity to various surface ground-motion intensity measures and site-condition proxies using a neural network approach

The impact of non-linear soil behavior on site response may be described by the non-linear to linear site response ratio RSRNL introduced in Régnier et al. (2013). This ratio most often exhibits a typical shape with an amplitude above one below a site-specific frequency fNL, and an amplitude below one beyond fNL. This paper presents an investigation of the correlation between this RSRNL ratio and various parameters used to characterize the site (Site Condition Proxies: SCPs) and the seismic loading level (Ground Motion Intensity Measures: GMIMs).The data used in this analysis come from sites of the Japanese Kiban–Kyoshin (KiK-net) network, for which the nonlinear to linear site-response ratio (RSRNL) is obtained by comparing the surface/down-hole Fourier spectral ratio for strong events and for weak events. The five SCPs are VS30, the minimum velocity of the soil profile (Vsmin), an index of the velocity gradient over the top 30 m (B30), the fundamental frequency f0HV, as measured from the H/V earthquake ratio, and the corresponding amplitude A0HV. The seven GMIMs are PGA, PGV, PGV/VS30 (peak strain proxy), IA (Arias Intensity), CAV (Cumulative Absolute Velocity), arms (Root Mean Square Acceleration) and Trifunac-Brady Duration (DT). The original data set consists of a total of 2927 RSRNL derived from KiK-net recordings at 132 sites. To assign an equal weight to each site, and to avoid any bias linked to sites with many recordings, for each GMIM, this original data set is grouped in 15 different intervals corresponding to fixed fractiles of the statistical distribution of the considered GMIM (every 10% from F10 to F50, and every 5% from F55 to F100). In each group, the average RSRNL-GM for each site is computed. For each of these seven advanced data sets, a neural network approach is used to predict the behavior of RSRNL-GM as a function of the corresponding GMIM, and one or two SCPs. The performance of each model is quantified through the average variance reduction coefficient μ(Rc) in a fixed frequency range. This sensitivity study is performed in the normalized frequency (f/fNL) domain to identify the best combinations (GMIM, SCPs) providing the largest variance reduction, and then in the absolute frequency domain for the final optimal combination. The optimal combinations [GMIM, two-SCPs] are triplets [PGV/VS30, VS30-f0HV; μ(Rc) = 18.6%], [PGV/VS30, VS30-A0HV; μ(Rc) = 18.16%], [PGV, VS30-f0HV; μ(Rc) = 17.3%] and [PGA, B30-A0HV; μ(Rc) = 17.2%]. The final absolute frequency model with the best triplet makes it possible to predict the non-linear response of a given site knowing its linear, weak-motion response, and two site proxy parameters, for wide ranges of the considered ground motion parameters.

Dynamic Community Evolution Analysis Framework for Large-Scale Complex Networks Based on Strong and Weak Events

Community evolution remains a heavily researched and challenging area in the analysis of dynamic complex network structures. Currently, the primary limitation of traditional event-based approaches for community evolution analysis is the lack of strict constraint conditions for distinguishing evolutionary events, which entails that as the cardinality of discovered events increases, so does the number of redundant events. Another limitation of existing approaches is the lack of consideration for weak events. Weak events can be generated by small changes in communities, which are empirically prevalent, and are typically not captured by traditional events. To manage these two aforementioned limitations, this research aims to formalize a weak and strong events-based framework, which includes the following newly discovered events: “weak shrink,” “weak expand,” “weak merge,” and “weak splity” predicated on the community overlapping degree and community degree membership, this article refines these traditional strong events, as well as new constraints for weak events. In addition, a community evolution mining framework, which is based on both strong and weak events, is proposed and denoted by a weak-event-based community evolution method (WECEM). The framework can be summarized by the following: 1) communities in complex networks with adjacent time-stamps are compared to determine the community overlapping degree and community membership degree; 2) the values of the community overlapping degree and membership degree meet the definition of events; and 3) weak events are effectively identified. Extensive experimental results, on real and synthetic data sets consisting of dynamic complex networks and online social networks, demonstrate that WECEM is able to identify weak events more effectively than traditional frameworks. Specifically, WECEM outperforms traditional frameworks by 22.9% in the number of discovered strong events. The detection accuracy of evolutionary events is approximately 12.2% higher than that of traditional event-based frameworks. It is also worth noting that, as the cardinality of the data grows, the proposed framework, when compared with traditional frameworks, can more effectively, and efficiently, mine large-scale complex networks.

Seismic Waveform Classification Based on Multi-classification Model Weighted Voting Method

The earthquake event is caused by the activity of the interior earth, which has the potential and can create great damage. Thus, in big data era, it is necessary to fast, efficient and universal automatic recognition and classification of seismic waveform. A well-performed recognition and classification algorithm should be sensitive to small and weak events with various waveform shapes, robust to background noise and non-seismic signals, and effective for processing a large number of data in different areas. In this paper, we introduce the weighted voting method in ensemble learning, taking 50000 seismic signals monitored by the capital circle and its nearby stations as training and testing data, we learn the main time-frequency characteristics of seismic positions in the three-component seismic signal data through the sub-model, and then identify and classify them. Finally, the classification score of the sub-model is weighted to confirm the final event type. Compared with single machine learning models, our result shows improved recognition and classification performance and reduced uncertainty of ensembles.

О сброшенных напряжениях в очагах землетрясений Северной Евразии и приведенной сейсмической энергии

A generalization of the results on the stress drop and the specific seismic energy for the earthquakes in Northern Eurasia has been made. The relationship of these parameters with the seismic moment and the magnitude has been analyzed. Detailed studies for the Northern Tien Shan (Bishkek geodynamic polygon) were carried out, the values of the dynamic parameters of the sources for 183 earthquakes of various energy classes (K = 8.7–14.8) were obtained: angular frequency, spectral density parameter, scalar seismic moment, source radius, stress drop level, seismic energy and specific seismic energy. Two models have been used to compute the source radius and the stress drop – the Brune approach and the improved Madariaga–Kaneko–Shearer model. For relatively weak events, a power-law dependence (regression) of the stress drop on the scalar seismic moment M0 has been identified, that complies with the results on the power-law dependence of the specific seismic energy on M0 in a number of other regions of Northern Eurasia. The relationship between the type of source movement and the stress drop level has been noted as well.

Stable Modification of Frequency–Magnitude Relation and Prospects for Its Application in Seismic Zoning

A new composite model is suggested for the frequency–magnitude relation of the earthquakes. The new model statistically reasonably describes the distribution in the range of weak and moderate events (the Gutenberg–Richter law) and in the range of strongest events (generalized Pareto law—one of the limiting laws in the extreme value theory). By the example of Japan and Kuriles, based on the GCMT catalog, it is shown that the model fairly adequately describes the seismicity in the circles containing at least 80 main shocks in the range of the reliably detected events m ≥ 5.3. The restriction on the number of the events imposes a statistical limitation on the resolution of the proposed model. In the case of the studied regions, this limitation allows reliable estimation of seismicity parameters for the areas with a radius of 300 km on a 2° × 2° grid. The use of this model in our previously designed statistical method for seismic risk assessment (Pisarenko and Rodkin, 2007; 2010; 2013) provides a theoretical basis for developing this technique towards more robust results and a better spatial resolution approaching the scale of the general seismic zoning maps.

Wintertime North American Weather Regimes and the Arctic Stratospheric Polar Vortex

AbstractThe impact of the Arctic stratospheric polar vortex on persistent weather regimes over North America is so far underexplored. Here we show the relationship between four wintertime North American weather regimes and the stratospheric vortex strength using reanalysis data. We find that the strength of the vortex significantly affects the behavior of the regimes. While a regime associated with Greenland blocking is strongly favored following weak vortex events, it is not the primary regime associated with a widespread, elevated risk of extreme cold in North America. Instead, we find that the regime most strongly associated with widespread extremely cold weather does not show a strong dependency on the strength of the lower stratospheric zonal mean zonal winds. We also suggest that stratospheric vortex morphology may be particularly important for cold air outbreaks during this regime.

A Two-Cool-Season Wind Profiler–Based Analysis of Westward-Directed Gap Flow through the Columbia River Gorge

Abstract This observational study of westward-directed gap flows through the Columbia River Gorge uses three radar wind profilers during two winter seasons between October 2015 and April 2017, with a focus on the gap-exit region at Troutdale, Oregon. Of the 92 gap-flow events identified at Troutdale, the mean duration was 38.5 h, the mean gap-jet speed was 12 m s−1, and the mean gap-flow depth was 570 m MSL. The mean gap-jet height and gap-flow depth were situated below the top of the inner gorge, while a maximum depth of 1087 m MSL was contained within the gorge’s outer-wall rim. The mean gap-flow depth was deepest in the cold-air source region east of the gorge and decreased westward to the coast. Strong gap-flow events were longer lived, deeper, and capped by stronger vertical shear than their weak counterparts, and strong (weak) events were forced primarily by a cold-interior anticyclone (offshore cyclone). Deep gap-flow events were longer lived, stronger, and had weaker capping vertical shear than shallow events, and represented a combination of gap-flow and synoptic forcing. Composite temporal analysis shows that gap-flow strength (depth) was maximized midevent (early event), freezing rain was most prevalent during the second half of the event, and accumulated precipitation was greatest late-event. Gap-flow events tended to begin (end) during the evening (morning) hours and were most persistent in January. Surface wind gusts and snow occurrences around Portland, Oregon, were associated primarily with the deepest gap flows, whereas freezing rain occurred predominantly during shallow gap flows.

A Correlation in the Waiting-time Distributions of Solar Flares

Abstract In a limited sample of isolated solar active regions, we find that the waiting times between flares may correlate well with flare magnitudes as determined by the GOES soft X-ray fluxes. A “build-up and release” scenario (BUR) for magnetic energy storage in the solar corona suggests the existence of such a relationship, relating the slowly varying subphotospheric energy sources to the sudden coronal energy releases of flares and CMEs. Substantial amounts of research effort had not previously found any obvious observational evidence for such a BUR process. This has posed a puzzle since coronal magnetic energy storage represents the consensus view of the basic flare mechanism. We have revisited the GOES soft X-ray flare statistics for any evidence of correlations, using two isolated active regions, and have found significant evidence for a “saturation” correlation. Rather than a “reset” form of this relaxation, in which the time before a flare correlates with its magnitude, the “saturation” relationship results in the time after the flare showing the correlation. The observed correlation competes with the “obscuration” effect of reduced GOES sensitivity following a strong event, by which weaker events can be under-reported systematically. This complicates the observed correlation, and we discuss several approaches to remedy this.

Intra‐seasonal characteristics of wintertime extreme cold events over South Korea

AbstractIn this study, the characteristics of extreme cold events over South Korea in the boreal winter (November to March) are investigated in terms of month‐to‐month variations of frequency, duration, amplitude, and atmospheric circulation pattern. To explain the mechanism for these month‐to‐month variations, all extreme cold events are classified into three types based on an agglomerative hierarchical clustering method, and their linkages with large‐scale variabilities, such as the Siberian High (SH), the Arctic Oscillation (AO), and the Madden–Julian Oscillation (MJO), are analysed. “Wave‐train” type does not tend to occur under the typical favourable conditions for the East Asian cold extremes, e.g., strong SH intensity, strong negative AO phase, and MJO phases 2–3, hence resulting in weak and short events. On the other hand, strong and long‐lasting “Ural blocking” and “subarctic blocking” types are accompanied with the aforementioned favourable large‐scale conditions. Thus, November and March with the most frequent occurrences of the wave‐train type are the months in which extreme cold events have weaker amplitude and shorter duration than other months. Compared with the wave‐train type, the Ural blocking type occur frequently in January and February, while occurrences of the subarctic blocking type are concentrated in December and January. It contributes to relatively powerful and sustained extreme cold events in mid‐winter (from December to February). In particular, extreme cold events during March have the lowest frequency, weakest amplitude, and shortest duration due to a lack of strong SH activity, strong negative AO phase, and MJO phases 2–3, but strong activities of these factors in January force the most frequent, strongest, and longest extreme cold events in the boreal winter.

A new model suite to determine the influence of cosmic rays on (exo)planetary atmospheric biosignatures

Context. The first opportunity to detect indications for life outside of the Solar System may be provided already within the next decade with upcoming missions such as the James Webb Space Telescope (JWST), the European Extremely Large Telescope (E-ELT) and the Atmospheric Remote-sensing Infrared Exoplanet Large-survey (ARIEL) mission, searching for atmospheric biosignatures on planets in the habitable zone of cool K- and M-stars. Nevertheless, their harsh stellar radiation and particle environment could lead to photochemical loss of atmospheric biosignatures. Aims. We aim to study the influence of cosmic rays on exoplanetary atmospheric biosignatures and the radiation environment considering feedbacks between energetic particle precipitation, climate, atmospheric ionization, neutral and ion chemistry, and secondary particle generation. Methods. We describe newly combined state-of-the-art modeling tools to study the impact of the radiation and particle environment, in particular of cosmic rays, on atmospheric particle interaction, atmospheric chemistry, and the climate-chemistry coupling in a self-consistent model suite. To this end, models like the Atmospheric Radiation Interaction Simulator (AtRIS), the Exoplanetary Terrestrial Ion Chemistry model (ExoTIC), and the updated coupled climate-chemistry model are combined. Results. In addition to comparing our results to Earth-bound measurements, we investigate the ozone production and -loss cycles as well as the atmospheric radiation dose profiles during quiescent solar periods and during the strong solar energetic particle event of February 23, 1956. Further, the scenario-dependent terrestrial transit spectra, as seen by the NIR-Spec infrared spectrometer onboard the JWST, are modeled. Amongst others, we find that the comparatively weak solar event drastically increases the spectral signal of HNO3, while significantly suppressing the spectral feature of ozone. Because of the slow recovery after such events, the latter indicates that ozone might not be a good biomarker for planets orbiting stars with high flaring rates.

Two-dimensional mineral dust radiative effect calculations from CALIPSO observations over Europe

Abstract. A demonstration study to examine the feasibility of retrieving dust radiative effects based on combined satellite data from MODIS (Moderate Resolution Imaging Spectroradiometer), CERES (Clouds and the Earth's Radiant Energy System) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar vertical profiles along their orbit is presented. The GAME (Global Atmospheric Model) radiative transfer model is used to estimate the shortwave and longwave dust radiative effects below the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite) orbit assuming an aerosol parameterization based on the CALIOP vertical distribution at a horizontal resolution of 5 km and additional AERONET (Aerosol Robotic Network) data. Two study cases are analyzed: a strong long-range transport mineral dust event (aerosol optical depth, AOD, of 0.52) that originated in the Sahara Desert and reached the United Kingdom and a weaker event (AOD = 0.16) that affected eastern Europe. The radiative fluxes obtained are first validated in terms of radiative efficiency at a single point with space–time colocated lidar ground-based measurements from EARLINET (European Aerosol Research Lidar Network) stations below the orbit. The methodology is then applied to the full orbit. The strong dependence of the radiative effects on the aerosol load (and to a lesser extent on the surface albedo) highlights the need for accurate AOD measurements for radiative studies. The calculated dust radiative effects and heating rates below the orbits are in good agreement with previous studies of mineral dust, with the radiative efficiency obtained at the surface ranging between −80.3 and −63.0 W m−2 for lower dust concentration event and −119.1 and −79.3 W m−2 for the strong event. Thus, results demonstrate the validity of the method presented here to retrieve 2-D accurate radiative properties with large spatial and temporal coverage.