First results from temporary deployment of small seismic network following the Mw=6.4 Petrinja earthquake

<p>The Department of Geophysics, University of Zagreb and the Italian National Institute of Oceanography and Applied Geophysics (OGS) installed on January 4th 2021, five temporary seismic stations near the town of Petrinja, Croatia, in the aftermath of  the 29 Decembre 2020 Mw 6.4 earthquake. The stations equipped with a seismometer and a strong motion sensor, recorded the aftershock sequence beginning six days after the mainshock allowing to augment the permanent seismic network in the area improving the azimuthal coverage and providing additional near‐field observations.</p><p>In this presentation we summarize the motivation and goals of the deployment; details regarding the station installation, instrumentation, and configurations and observations from the network. The collected data set will be useful for carrying out several seismological studies including the analysis of variability of strong ground motions in near field, the determination of the aftershocks source parameters,  the estimation (if any) of rupture directivity of small events, the clustering of events in space and time, the better imaging of the fault zone, the evolution of crustal properties within and outside of the fault zone.</p>

The effect of imposed production measures on gas extraction induced seismic risk

Shaking and damage in the province of Groningen, the Netherlands, resulting from production-induced seismicity has caused increased public anxiety. Since 2014, production offtake has been reduced stepwise by over 50% in an attempt to minimise production-induced seismicity. The earthquake catalogue, combined with comprehensive data of the changes in production offtake, shows a clear response of seismic activity following the production measures taken. Associated temporal variations in the proportionality between smaller- and larger-magnitude events (the b-value of the Gutenberg–Richter relation) are observed. Since production measures were imposed, the b-value has tended to increase, thus lowering the probability of a larger-magnitude event. The analysis also shows increases in activity rate and b-value prior to larger-magnitude events. Subsequently, the probability of a larger-magnitude event seems to be decreasing prior to the events occurring. This implies that for short-term earthquake prediction of hydrocarbon-production-induced seismicity, these types of analysis could be misleading. However, regional analysis is necessary to explain the observations in terms of rupture initiation. At present, each event felt still draws the interest of both public and press. As some clustering of events in both time and space is still observed, managing both the seismicity and the public perception provides a continuing challenge.

On the clustering of winter storm loss events over Germany

During the last decades, several windstorm series hit Europe leading to large aggregated losses. Such storm series are examples of serial clustering of extreme cyclones, presenting a considerable risk for the insurance industry. Clustering of events and return periods of storm series for Germany are quantified based on potential losses using empirical models. Two reanalysis datasets and observations from German weather stations are considered for 30 winters. Histograms of events exceeding selected return levels (1, 2 and 5 year) are derived. Return periods of historical storm series are estimated based on the Poisson and the negative Binomial distributions. Over 4000 years of global circulation model simulations forced with current climate conditions are analysed to provide a better assessment of historical return periods. Estimations differ between distributions, for example 40 to 65 years for the 1990 series. For such less frequent series, estimates obtained with the Poisson distribution clearly deviate from empirical data. The negative Binomial distribution provides better estimates, even though a sensitivity to return level and dataset is identified. The consideration of GCM data permits a strong reduction of uncertainties. The present results support the importance of considering explicitly clustering of losses for an adequate risk assessment for economical applications.

Arctic rapid sea ice loss events in regional coupled climate scenario experiments

Rapid sea ice loss events (RILEs) in a mini-ensemble of regional Arctic coupled climate model scenario experiments are analyzed. Mechanisms of sudden ice loss are strongly related to atmospheric circulation conditions and preconditioning by sea ice thinning during the seasons and years before the event. Clustering of events in time suggests a strong control by large-scale atmospheric circulation. Anomalous atmospheric circulation is providing warm air anomalies of up to 5 K and is forcing ice flow, affecting winter ice growth. Even without a seasonal preconditioning during winter, ice drop events can be initiated by anomalous inflow of warm air during summer. It is shown that RILEs can be generated based on atmospheric circulation changes as a major driving force without major competing mechanisms, other than occasional longwave effects during spring and summer. Other anomalous seasonal radiative forcing or short-lived forcers (e.g., soot) play minor roles or no role at all in our model. RILEs initiated by ocean forcing do not occur in the model, although cannot be ruled out due to model limitations. Mechanisms found are qualitatively in line with observations of the 2007 RILE.

Arctic rapid sea ice loss events in regional coupled climate scenario experiments

Rapid sea ice loss events (RILEs) in a mini-ensemble of regional Arctic coupled climate model scenario experiments are analyzed. Mechanisms of sudden ice loss are strongly related to atmospheric circulation conditions and preconditioning by sea ice thinning during the seasons and years before the event. Clustering of events in time suggests a strong control by large scale atmospheric circulation. Anomalous atmospheric circulation is forcing ice flow and providing warm air affecting winter ice growth. Even without a seasonal preconditioning during winter, ice drop events can be initiated by anomalous inflow of warm air from the Atlantic sector during summer. It is shown that RILE events can be generated solely based on atmospheric circulation changes without possible competing mechanisms, such as anomalous seasonal radiative forcing or short-lived forcers (e.g. soot). Such forces do merely play minor roles or no role at all in our model. Mechanisms found are qualitatively in line with observations of the 2007 RILE.