ALBERT

Description: The evaluation of potential landslides in mountain areas is a very complex process. Currently, event understanding is scarce due to information limitations. Identifying the whole chain of events is not a straightforward task, and the impacts of mass-wasting processes depend on the conditions downstream of the origin. In this paper, we present an example that illustrates the complexities in the evaluation of the chain of events that may lead to a natural disaster. On 16 December 2017, a landslide occurred in the Yelcho mountain range (southern Chile). In that event, 7 million m3 of rocks and soil fell on the Yelcho glacier, depositing 2 million m3 on the glacier terminal, and the rest continued downstream, triggering a mudflow that hit Villa Santa Lucía in Chilean Patagonia and killing 22 people. The complex event was anticipated in the region by the National Geological and Mining Survey (Sernageomin in Spanish). However, the effects of the terrain characteristics along the run-out area were more significant than anticipated. In this work, we evaluate the conditions that enabled the mudflow that hit Villa Santa Lucía. We used the information generated by Sernageomin's professionals after the mudflow. We carried out geotechnical tests to characterize the soil. We simulated the mudflow using two hydrodynamic programs (r.avaflow and Flo-2D) that can handle the rheology of the water–soil mixture. Our results indicate that the soil is classified as volcanic pumices. This type of soil can be susceptible to the collapse of the structure when subjected to shearing (molding), flowing as a viscous liquid. From the numerical modeling, we concluded that r.avaflow performs better than Flo-2D. The mudflow was satisfactorily simulated using a water content in the mixture ranging from 30 % to 40 %, which would have required a source of about 3 million m3 of water. Coupling the simulations and the soil tests that we performed, we estimated that in the area scoured by the mudflow, there were probably around 2 800 000 m3 of water within the soil. Therefore, the conditions of the valley were crucial to enhancing the impacts of the landslide. This result is relevant because it highlights the importance of evaluating the complete chain of events to map hazards. We suggest that in future hazard mapping, geotechnical studies in combination with hydrodynamic simulation should be included, in particular when human lives are at risk.

Description: In the framework of the EU Copernicus programme, the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the Joint Research Centre (JRC) is forecasting daily fire weather indices using its medium-range ensemble prediction system. The use of weather forecasts in place of local observations can extend early warnings by up to 1–2 weeks, allowing for greater proactive coordination of resource-sharing and mobilization within and across countries. Using 1 year of pre-operational service in 2017 and the Fire Weather Index (FWI), here we assess the capability of the system globally and analyse in detail three major events in Chile, Portugal and California. The analysis shows that the skill provided by the ensemble forecast system extends to more than 10 d when compared to the use of mean climate, making a case for extending the forecast range to the sub-seasonal to seasonal timescale. However, accurate FWI prediction does not translate into accuracy in the forecast of fire activity globally. Indeed, when all fires detected in 2017 are considered, including agricultural- and human-induced burning, high FWI values only occur in 50 % of the cases and are limited to the Boreal regions. Nevertheless for very large events which were driven by weather conditions, FWI forecasts provide advance warning that could be instrumental in setting up management and containment strategies.

Description: In the past decades, severe heat waves have frequently occurred in many parts of the world. These conspicuous heat waves exerted terrible influences on human health, society, the economy, agriculture, the ecosystem and so on. Based on observed daily temperatures in China, an integrated index of heat waves and extreme-temperature days was established involving the frequency, duration, intensity and scale of these events across large cities in China. Heat waves and extreme-temperature days showed an increasing trend in most regions except northwest China from 1955 to 2014. After the late 1980s, the increasing trend was more obvious than the decades before. The cities in the middle and lower reaches of the Yangtze River were threatened by the most serious heat events in the past 60 years, especially Chongqing and Changsha. Due to the subtropical monsoon climate and special terrain, Chongqing experienced the most heat events in a long period of time. In particular, there was obvious fluctuation of hot years in 31 cities, which did not continuously rise with global warming; 21 cities mainly located in the eastern and southern regions of China had an obvious rising trend; eight cities had a clear declining trend which was mainly distributed in the western and northern regions of China; and there were no extreme-temperature days in Kunming and Lhasa in the past 60 years. The study revealed an obvious differentiation of heat events for 31 cities under climate change; heat threat in most cities is increasing but declining or remaining unchanged in the other cities. The trend is likely to intensify with global warming.

Description: Storm tides are a major hazard for the German North Sea coasts. For coastal protection and economic activities, planning information on the probability and magnitude of extreme storm tides and their possible future changes is important. This study focuses on the most extreme events and examines whether they could have become more severe under slightly different conditions while still remaining within physical plausibility. In the face of a limited number of observational data on very severe events, an extensive set of model data is used to extract most extreme storm tide events for locations in the German Bight, in particular Borkum and the Ems estuary. The data set includes water levels and respective atmospheric conditions from a hindcast and future climate realizations without sea level rise describing today's and possible future conditions. A number of very severe events with water levels exceeding those measured near Borkum since 1906 are identified in the data set. A possible further amplification of the highest events is investigated by simulating these events for the North Sea with different phase lags between the astronomical tide given at the open model boundaries and the wind forcing. It is found that superposition of spring tide conditions, different timing of the astronomical high water and atmospheric conditions during the highest storm event would cause an enhancement of the highest water level up to about 50 cm. The water levels of the two highest events from the data set are used to analyse the effects in the Ems estuary using a high-resolution model of the German Bight. Additionally, the influences of an extreme river runoff and of sea level rise are studied. The extreme river runoff of 1200 m3 s−1 increases the highest water levels by several decimetres in the narrow upstream part of the Ems estuary. This effect diminishes downstream. The sea level rise increases the water level in the downstream part of the Ems estuary by the amount applied at the model boundary to the North Sea. In the upstream part, its influence on the water level decreases. This study may serve as a first step towards an impact assessment for severe storm tides and towards implications for coastal zone management in times of climate change.

Description: Snow instability tests provide valuable information regarding the stability of the snowpack. Test results are key data used to prepare public avalanche forecasts. However, to include them into operational procedures, a quantitative interpretation scheme is needed. Whereas the interpretation of the rutschblock test (RB) is well established, a similar detailed classification for the extended column test (ECT) is lacking. Therefore, we develop a four-class stability interpretation scheme. Exploring a large data set of 1719 ECTs observed at 1226 sites, often performed together with a RB in the same snow pit, and corresponding slope stability information, we revisit the existing stability interpretations and suggest a more detailed classification. In addition, we consider the interpretation of cases when two ECTs were performed in the same snow pit. Our findings confirm previous research, namely that the crack propagation propensity is the most relevant ECT result and that the loading step required to initiate a crack is of secondary importance for stability assessment. The comparison with the RB showed that the ECT classifies slope stability less reliably than the RB. In some situations, performing a second ECT may be helpful when the first test did not indicate rather unstable or stable conditions. Finally, the data clearly show that false-unstable predictions of stability tests outnumber the correct-unstable predictions in an environment where overall unstable locations are rare.

Description: On 5 March 2019 12:00 UTC, an atmospheric river (AR) made landfall in Santa Barbara, CA, and lasted approximately 30 h. While ARs are typical winter storms in the area, the extraordinary number of lightning strikes observed near coastal Santa Barbara made this event unique. The Earth Networks Global Lightning Network (ENGLN) detected 8811 lightning flashes around southern California (30 to 37∘ N and 130 to 115∘ W) in 24 h, which is roughly 2500 times the climatological flash rate in this region. The AR-related thunderstorm resulted in approximately 23.18 mm accumulated precipitation in 30 h in Santa Barbara. This article examines synoptic and mesoscale features conducive to this electrifying AR event, characterizing its uniqueness in the context of previous March events that made landfall in the region. We show that this AR was characterized by an unusual deep moist layer extending from the low to mid-troposphere in an environment with potential instability and low-elevation freezing level. Despite the negligible convective available potential energy (CAPE) during the peak of the thunderstorm near Santa Barbara, the lifting of layers with high water vapor content in the AR via warm conveyor belt and orographic forcing in a convectively unstable atmosphere resulted in the formation of hail and enhanced electrification.

Description: A number of seaside communities in Troms, northern Norway, are vulnerable to sudden weather-induced access disruptions due to high-impact weather and dependency on one or few roads. In this paper we study changes in winter weather known to potentially cause access disruptions in Troms, for the present climate (1958–2017) and two future periods (2041–2070; 2071–2100). We focus on climate indices associated with snow avalanches and weather that may lead to for example slippery road conditions. In two focus areas, the most important results show larger snow amounts now compared to 50 years ago, and heavy snowfall has become more intense and frequent. This trend is expected to turn in the future, particularly at low elevations where snow cover during winter might become a rarity by 2100. Strong snow drift, due to a combination of snowfall and wind speed, has slightly increased in the two focus areas, but a strong decrease is expected in the future due to less snow. Events of heavy rain during winter are rather infrequent in the present winter climate of Troms, but we show that these events are likely to occur much more often in all regions in the future.

Description: Statistical detection and modeling of the over-dispersion of winter storm occurrence Natural Hazards and Earth System Science, 15, 1757-1761, 2015 Author(s): M. Raschke In this communication, I improve the detection and modeling of the over-dispersion of winter storm occurrence. For this purpose, the generalized Poisson distribution and the Bayesian information criterion are introduced; the latter is used for statistical model selection. Moreover, I replace the frequently used dispersion statistics by an over-dispersion parameter which does not depend on the considered return period of storm events. These models and methods are applied in order to properly detect the over-dispersion in winter storm data for Germany, carrying out a joint estimation of the distribution models for different samples.

Description: Impacts on wave-driven harbour agitation due to climate change in Catalan ports Natural Hazards and Earth System Science, 15, 1695-1709, 2015 Author(s): J. P. Sierra, M. Casas-Prat, M. Virgili, C. Mösso, and A. Sánchez-Arcilla The objective of the present work is to analyse how changes in wave patterns due to the effect of climate change can affect harbour agitation (oscillations within the port due to wind waves). The study focuses on 13 harbours located on the Catalan coast (NW Mediterranean) using a methodology with general applicability. To obtain the patterns of agitation, a Boussinesq-type model is used, which is forced at the boundaries by present/future offshore wave conditions extracted from recently developed high-resolution wave projections in the NW Mediterranean. These wave projections were obtained with the SWAN model forced by present/future surface wind fields projected, respectively, by five different combinations of global and regional circulation models (GCMs and RCMs) for the A1B scenario. The results show a general slight reduction in the annual average agitation for most of the ports, except for the northernmost and southernmost areas of the region, where a slight increase is obtained. A seasonal analysis reveals that the tendency to decrease is accentuated in winter. However, the inter-model variability is large for both the winter and the annual analysis. Conversely, a general increase with a larger agreement among models is found during summer, which is the period with greater activity in most of the studied ports (marinas). A qualitative assessment of the factors of variability seems to indicate that the choice of GCM tends to affect the spatial pattern, whereas the choice of RCM induces a more homogeneous bias over the regional domain.

Description: Towards predictive data-driven simulations of wildfire spread – Part II: Ensemble Kalman Filter for the state estimation of a front-tracking simulator of wildfire spread Natural Hazards and Earth System Science, 15, 1721-1739, 2015 Author(s): M. C. Rochoux, C. Emery, S. Ricci, B. Cuenot, and A. Trouvé This paper is the second part in a series of two articles, which aims at presenting a data-driven modeling strategy for forecasting wildfire spread scenarios based on the assimilation of the observed fire front location and on the sequential correction of model parameters or model state. This model relies on an estimation of the local rate of fire spread (ROS) as a function of environmental conditions based on Rothermel's semi-empirical formulation, in order to propagate the fire front with an Eulerian front-tracking simulator. In Part I, a data assimilation (DA) system based on an ensemble Kalman filter (EnKF) was implemented to provide a spatially uniform correction of biomass fuel and wind parameters and thereby, produce an improved forecast of the wildfire behavior (addressing uncertainties in the input parameters of the ROS model only). In Part II, the objective of the EnKF algorithm is to sequentially update the two-dimensional coordinates of the markers along the discretized fire front, in order to provide a spatially distributed correction of the fire front location and thereby, a more reliable initial condition for further model time-integration (addressing all sources of uncertainties in the ROS model). The resulting prototype data-driven wildfire spread simulator is first evaluated in a series of verification tests using synthetically generated observations; tests include representative cases with spatially varying biomass properties and temporally varying wind conditions. In order to properly account for uncertainties during the EnKF update step and to accurately represent error correlations along the fireline, it is shown that members of the EnKF ensemble must be generated through variations in estimates of the fire's initial location as well as through variations in the parameters of the ROS model. The performance of the prototype simulator based on state estimation (SE) or parameter estimation (PE) is then evaluated by comparison with data taken from a reduced-scale controlled grassland fire experiment. Results indicate that data-driven simulations are capable of correcting inaccurate predictions of the fire front location and of subsequently providing an optimized forecast of the wildfire behavior at future lead times. The complementary benefits of both PE and SE approaches, in terms of analysis and forecast performance, are also emphasized. In particular, it is found that the size of the assimilation window must be specified adequately with the persistence of the model initial condition and/or with the temporal and spatial variability of the environmental conditions in order to track sudden changes in wildfire behavior. The present prototype data-driven forecast system is still at an early stage of development. In this regard, this preliminary investigation provides valuable information on how to combine observations with a fire spread model in an efficient way, as well as guidelines to design the future system evolution in order to meet the operational requirements of wildfire spread monitoring.